diff --git a/01_materials/labs/01_setup.ipynb b/01_materials/labs/01_setup.ipynb
index 6b0966a70..b77088901 100644
--- a/01_materials/labs/01_setup.ipynb
+++ b/01_materials/labs/01_setup.ipynb
@@ -302,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -312,7 +312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -322,9 +322,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-23 21:11:17,843, 530896887.py, 3, INFO, Hello world!\n"
+     ]
+    }
+   ],
    "source": [
     "from logger import get_logger\n",
     "_logs = get_logger(__name__)\n",
@@ -425,7 +433,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "env",
+   "display_name": "dsi_participant",
    "language": "python",
    "name": "python3"
   },
@@ -439,7 +447,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/01_materials/labs/02_data_engineering.ipynb b/01_materials/labs/02_data_engineering.ipynb
index 2d3205c27..879dd5de5 100644
--- a/01_materials/labs/02_data_engineering.ipynb
+++ b/01_materials/labs/02_data_engineering.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -107,7 +107,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +129,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -152,9 +152,130 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing JCI\n",
+      "Downloaded (2558, 9).\n",
+      "Processing BSX\n",
+      "Downloaded (2558, 9).\n",
+      "Processing LIN\n",
+      "Downloaded (2558, 9).\n",
+      "Processing DOW\n",
+      "Downloaded (1226, 9).\n",
+      "Processing CVX\n",
+      "Downloaded (2558, 9).\n",
+      "Processing KHC\n",
+      "Downloaded (2159, 9).\n",
+      "Processing RL\n",
+      "Downloaded (2558, 9).\n",
+      "Processing ED\n",
+      "Downloaded (2558, 9).\n",
+      "Processing BX\n",
+      "Downloaded (2558, 9).\n",
+      "Processing IBM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing A\n",
+      "Downloaded (2558, 9).\n",
+      "Processing FIS\n",
+      "Downloaded (2558, 9).\n",
+      "Processing MAS\n",
+      "Downloaded (2558, 9).\n",
+      "Processing CPB\n",
+      "Downloaded (2558, 9).\n",
+      "Processing PNW\n",
+      "Downloaded (2558, 9).\n",
+      "Processing QCOM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing YUM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing AWK\n",
+      "Downloaded (2558, 9).\n",
+      "Processing MU\n",
+      "Downloaded (2558, 9).\n",
+      "Processing RCL\n",
+      "Downloaded (2558, 9).\n",
+      "Processing WTW\n",
+      "Downloaded (2558, 9).\n",
+      "Processing GWW\n",
+      "Downloaded (2558, 9).\n",
+      "Processing HAS\n",
+      "Downloaded (2558, 9).\n",
+      "Processing PEAK\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "$PEAK: possibly delisted; No timezone found\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No data for PEAK\n",
+      "Processing BR\n",
+      "Downloaded (2558, 9).\n",
+      "Processing VLO\n",
+      "Downloaded (2558, 9).\n",
+      "Processing VICI\n",
+      "Downloaded (1530, 9).\n",
+      "Processing RHI\n",
+      "Downloaded (2558, 9).\n",
+      "Processing CRL\n",
+      "Downloaded (2558, 9).\n",
+      "Processing NEM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing LYB\n",
+      "Downloaded (2558, 9).\n",
+      "Processing GS\n",
+      "Downloaded (2558, 9).\n",
+      "Processing V\n",
+      "Downloaded (2558, 9).\n",
+      "Processing EPAM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing ABT\n",
+      "Downloaded (2558, 9).\n",
+      "Processing NFLX\n",
+      "Downloaded (2558, 9).\n",
+      "Processing KVUE\n",
+      "Downloaded (187, 9).\n",
+      "Processing BKNG\n",
+      "Downloaded (2558, 9).\n",
+      "Processing IT\n",
+      "Downloaded (2558, 9).\n",
+      "Processing BBY\n",
+      "Downloaded (2558, 9).\n",
+      "Processing NUE\n",
+      "Downloaded (2558, 9).\n",
+      "Processing CBRE\n",
+      "Downloaded (2558, 9).\n",
+      "Processing WDC\n",
+      "Downloaded (2558, 9).\n",
+      "Processing EXPE\n",
+      "Downloaded (2558, 9).\n",
+      "Processing AMGN\n",
+      "Downloaded (2558, 9).\n",
+      "Processing BRO\n",
+      "Downloaded (2558, 9).\n",
+      "Processing MMM\n",
+      "Downloaded (2558, 9).\n",
+      "Processing ABNB\n",
+      "Downloaded (789, 9).\n",
+      "Processing MDT\n",
+      "Downloaded (2558, 9).\n",
+      "Processing AMZN\n",
+      "Downloaded (2558, 9).\n",
+      "Final shape (118443, 9).\n"
+     ]
+    }
+   ],
    "source": [
     "# List to hold final results\n",
     "px_list = list()\n",
@@ -221,7 +342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -239,7 +360,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -248,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -259,9 +380,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Writing to dt ((118443, 9))csv took 0.7448451519012451 seconds.\n",
+      "Csv file size 14.036881 MB\n"
+     ]
+    }
+   ],
    "source": [
     "start = time.time()\n",
     "px_dt.to_csv(stock_path, index = False)\n",
@@ -286,18 +416,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1669/676544213.py:1: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \n",
+      "In a future release, Dask DataFrame will use new implementation that\n",
+      "contains several improvements including a logical query planning.\n",
+      "The user-facing DataFrame API will remain unchanged.\n",
+      "\n",
+      "The new implementation is already available and can be enabled by\n",
+      "installing the dask-expr library:\n",
+      "\n",
+      "    $ pip install dask-expr\n",
+      "\n",
+      "and turning the query planning option on:\n",
+      "\n",
+      "    >>> import dask\n",
+      "    >>> dask.config.set({'dataframe.query-planning': True})\n",
+      "    >>> import dask.dataframe as dd\n",
+      "\n",
+      "API documentation for the new implementation is available at\n",
+      "https://docs.dask.org/en/stable/dask-expr-api.html\n",
+      "\n",
+      "Any feedback can be reported on the Dask issue tracker\n",
+      "https://github.com/dask/dask/issues \n",
+      "\n",
+      "  import dask.dataframe as dd\n"
+     ]
+    }
+   ],
    "source": [
     "import dask.dataframe as dd"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Writing dd ((118443, 9)) to parquet took 0.6877284049987793 seconds.\n",
+      "Parquet file size 5.565733 MB\n"
+     ]
+    }
+   ],
    "source": [
     "px_dd = dd.from_pandas(px_dt, npartitions = len(tickers))\n",
     "parquet_path = os.path.join(temp, \"stock_px.parquet\")\n",
@@ -352,7 +521,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -365,7 +534,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -410,7 +579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -435,7 +604,19 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1669/3091835559.py:2: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .apply(func)\n",
+      "  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .apply(func, meta=('x', 'f8'))            for series result\n",
+      "  dd_rets = (dd_px.groupby('ticker', group_keys=False).apply(\n"
+     ]
+    }
+   ],
    "source": [
     "import numpy as np\n",
     "dd_rets = (dd_px.groupby('ticker', group_keys=False).apply(\n",
@@ -458,9 +639,158 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><strong>Dask DataFrame Structure:</strong></div>\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>Dividends</th>\n",
+       "      <th>Stock Splits</th>\n",
+       "      <th>year</th>\n",
+       "      <th>Close_lag_1</th>\n",
+       "      <th>returns</th>\n",
+       "      <th>positive_return</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>npartitions=49</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>datetime64[ns, America/New_York]</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>int64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>int32</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>int64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ABNB</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>\n",
+       "<div>Dask Name: assign, 18 graph layers</div>"
+      ],
+      "text/plain": [
+       "Dask DataFrame Structure:\n",
+       "                                            Date     Open     High      Low    Close Volume Dividends Stock Splits   year Close_lag_1  returns positive_return\n",
+       "npartitions=49                                                                                                                                                \n",
+       "A               datetime64[ns, America/New_York]  float64  float64  float64  float64  int64   float64      float64  int32     float64  float64           int64\n",
+       "ABNB                                         ...      ...      ...      ...      ...    ...       ...          ...    ...         ...      ...             ...\n",
+       "...                                          ...      ...      ...      ...      ...    ...       ...          ...    ...         ...      ...             ...\n",
+       "YUM                                          ...      ...      ...      ...      ...    ...       ...          ...    ...         ...      ...             ...\n",
+       "YUM                                          ...      ...      ...      ...      ...    ...       ...          ...    ...         ...      ...             ...\n",
+       "Dask Name: assign, 18 graph layers"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "dd_rets"
    ]
@@ -475,9 +805,281 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>Dividends</th>\n",
+       "      <th>Stock Splits</th>\n",
+       "      <th>year</th>\n",
+       "      <th>Close_lag_1</th>\n",
+       "      <th>returns</th>\n",
+       "      <th>positive_return</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ticker</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2013-12-02 00:00:00-05:00</td>\n",
+       "      <td>34.875483</td>\n",
+       "      <td>35.005930</td>\n",
+       "      <td>34.640675</td>\n",
+       "      <td>34.705898</td>\n",
+       "      <td>2039962</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2013-12-03 00:00:00-05:00</td>\n",
+       "      <td>34.516732</td>\n",
+       "      <td>34.679795</td>\n",
+       "      <td>34.281924</td>\n",
+       "      <td>34.523254</td>\n",
+       "      <td>3462706</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>34.705898</td>\n",
+       "      <td>-0.005263</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2013-12-04 00:00:00-05:00</td>\n",
+       "      <td>34.464560</td>\n",
+       "      <td>35.110283</td>\n",
+       "      <td>34.386293</td>\n",
+       "      <td>34.947220</td>\n",
+       "      <td>3377288</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>34.523254</td>\n",
+       "      <td>0.012281</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2013-12-05 00:00:00-05:00</td>\n",
+       "      <td>34.797202</td>\n",
+       "      <td>35.090711</td>\n",
+       "      <td>34.647187</td>\n",
+       "      <td>34.895039</td>\n",
+       "      <td>2530939</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>34.947220</td>\n",
+       "      <td>-0.001493</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2013-12-06 00:00:00-05:00</td>\n",
+       "      <td>35.064636</td>\n",
+       "      <td>35.827758</td>\n",
+       "      <td>35.064636</td>\n",
+       "      <td>35.762535</td>\n",
+       "      <td>4268513</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>34.895039</td>\n",
+       "      <td>0.024860</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>2024-01-25 00:00:00-05:00</td>\n",
+       "      <td>127.913548</td>\n",
+       "      <td>128.386458</td>\n",
+       "      <td>126.642582</td>\n",
+       "      <td>128.297791</td>\n",
+       "      <td>1871700</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>127.529305</td>\n",
+       "      <td>0.006026</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>2024-01-26 00:00:00-05:00</td>\n",
+       "      <td>128.002213</td>\n",
+       "      <td>128.760851</td>\n",
+       "      <td>126.770665</td>\n",
+       "      <td>127.184464</td>\n",
+       "      <td>1157000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>128.297791</td>\n",
+       "      <td>-0.008678</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>2024-01-29 00:00:00-05:00</td>\n",
+       "      <td>127.194317</td>\n",
+       "      <td>128.622910</td>\n",
+       "      <td>126.396261</td>\n",
+       "      <td>128.622910</td>\n",
+       "      <td>1482100</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>127.184464</td>\n",
+       "      <td>0.011310</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>2024-01-30 00:00:00-05:00</td>\n",
+       "      <td>128.435707</td>\n",
+       "      <td>129.283013</td>\n",
+       "      <td>127.667222</td>\n",
+       "      <td>128.691864</td>\n",
+       "      <td>1421500</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>128.622910</td>\n",
+       "      <td>0.000536</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YUM</th>\n",
+       "      <td>2024-01-31 00:00:00-05:00</td>\n",
+       "      <td>129.509619</td>\n",
+       "      <td>130.031795</td>\n",
+       "      <td>127.351944</td>\n",
+       "      <td>127.578560</td>\n",
+       "      <td>2154200</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>128.691864</td>\n",
+       "      <td>-0.008651</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>118443 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            Date        Open        High         Low  \\\n",
+       "ticker                                                                 \n",
+       "A      2013-12-02 00:00:00-05:00   34.875483   35.005930   34.640675   \n",
+       "A      2013-12-03 00:00:00-05:00   34.516732   34.679795   34.281924   \n",
+       "A      2013-12-04 00:00:00-05:00   34.464560   35.110283   34.386293   \n",
+       "A      2013-12-05 00:00:00-05:00   34.797202   35.090711   34.647187   \n",
+       "A      2013-12-06 00:00:00-05:00   35.064636   35.827758   35.064636   \n",
+       "...                          ...         ...         ...         ...   \n",
+       "YUM    2024-01-25 00:00:00-05:00  127.913548  128.386458  126.642582   \n",
+       "YUM    2024-01-26 00:00:00-05:00  128.002213  128.760851  126.770665   \n",
+       "YUM    2024-01-29 00:00:00-05:00  127.194317  128.622910  126.396261   \n",
+       "YUM    2024-01-30 00:00:00-05:00  128.435707  129.283013  127.667222   \n",
+       "YUM    2024-01-31 00:00:00-05:00  129.509619  130.031795  127.351944   \n",
+       "\n",
+       "             Close   Volume  Dividends  Stock Splits  year  Close_lag_1  \\\n",
+       "ticker                                                                    \n",
+       "A        34.705898  2039962        0.0           0.0  2013          NaN   \n",
+       "A        34.523254  3462706        0.0           0.0  2013    34.705898   \n",
+       "A        34.947220  3377288        0.0           0.0  2013    34.523254   \n",
+       "A        34.895039  2530939        0.0           0.0  2013    34.947220   \n",
+       "A        35.762535  4268513        0.0           0.0  2013    34.895039   \n",
+       "...            ...      ...        ...           ...   ...          ...   \n",
+       "YUM     128.297791  1871700        0.0           0.0  2024   127.529305   \n",
+       "YUM     127.184464  1157000        0.0           0.0  2024   128.297791   \n",
+       "YUM     128.622910  1482100        0.0           0.0  2024   127.184464   \n",
+       "YUM     128.691864  1421500        0.0           0.0  2024   128.622910   \n",
+       "YUM     127.578560  2154200        0.0           0.0  2024   128.691864   \n",
+       "\n",
+       "         returns  positive_return  \n",
+       "ticker                             \n",
+       "A            NaN                0  \n",
+       "A      -0.005263                0  \n",
+       "A       0.012281                1  \n",
+       "A      -0.001493                0  \n",
+       "A       0.024860                1  \n",
+       "...          ...              ...  \n",
+       "YUM     0.006026                1  \n",
+       "YUM    -0.008678                0  \n",
+       "YUM     0.011310                1  \n",
+       "YUM     0.000536                1  \n",
+       "YUM    -0.008651                0  \n",
+       "\n",
+       "[118443 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "dd_rets.compute()"
    ]
@@ -495,7 +1097,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -507,7 +1109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -561,7 +1163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -582,7 +1184,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -592,9 +1194,3586 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-23 21:12:13,623, data_manager.py, 43, INFO, Getting price data for all tickers.\n",
+      "2024-10-23 21:12:13,623, data_manager.py, 43, INFO, Getting price data for all tickers.\n",
+      "2024-10-23 21:12:13,628, data_manager.py, 52, INFO, Getting tickers from ../../05_src/data/tickers/sp500_wiki.csv\n",
+      "2024-10-23 21:12:13,628, data_manager.py, 52, INFO, Getting tickers from ../../05_src/data/tickers/sp500_wiki.csv\n",
+      "2024-10-23 21:12:13,632, data_manager.py, 58, INFO, Processing all tickers\n",
+      "2024-10-23 21:12:13,632, data_manager.py, 58, INFO, Processing all tickers\n",
+      "2024-10-23 21:12:13,634, data_manager.py, 73, INFO, Processing ticker MMM\n",
+      "2024-10-23 21:12:13,634, data_manager.py, 73, INFO, Processing ticker MMM\n",
+      "2024-10-23 21:12:13,635, data_manager.py, 108, INFO, Getting stock price data for MMM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:13,635, data_manager.py, 108, INFO, Getting stock price data for MMM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:14,036, data_manager.py, 82, INFO, Saving data for MMM by year\n",
+      "2024-10-23 21:12:14,036, data_manager.py, 82, INFO, Saving data for MMM by year\n",
+      "2024-10-23 21:12:15,498, data_manager.py, 73, INFO, Processing ticker AOS\n",
+      "2024-10-23 21:12:15,498, data_manager.py, 73, INFO, Processing ticker AOS\n",
+      "2024-10-23 21:12:15,501, data_manager.py, 108, INFO, Getting stock price data for AOS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:15,501, data_manager.py, 108, INFO, Getting stock price data for AOS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:15,761, data_manager.py, 82, INFO, Saving data for AOS by year\n",
+      "2024-10-23 21:12:15,761, data_manager.py, 82, INFO, Saving data for AOS by year\n",
+      "2024-10-23 21:12:17,216, data_manager.py, 73, INFO, Processing ticker ABT\n",
+      "2024-10-23 21:12:17,216, data_manager.py, 73, INFO, Processing ticker ABT\n",
+      "2024-10-23 21:12:17,219, data_manager.py, 108, INFO, Getting stock price data for ABT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:17,219, data_manager.py, 108, INFO, Getting stock price data for ABT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:17,599, data_manager.py, 82, INFO, Saving data for ABT by year\n",
+      "2024-10-23 21:12:17,599, data_manager.py, 82, INFO, Saving data for ABT by year\n",
+      "2024-10-23 21:12:18,946, data_manager.py, 73, INFO, Processing ticker ABBV\n",
+      "2024-10-23 21:12:18,946, data_manager.py, 73, INFO, Processing ticker ABBV\n",
+      "2024-10-23 21:12:18,947, data_manager.py, 108, INFO, Getting stock price data for ABBV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:18,947, data_manager.py, 108, INFO, Getting stock price data for ABBV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:19,176, data_manager.py, 82, INFO, Saving data for ABBV by year\n",
+      "2024-10-23 21:12:19,176, data_manager.py, 82, INFO, Saving data for ABBV by year\n",
+      "2024-10-23 21:12:19,797, data_manager.py, 73, INFO, Processing ticker ACN\n",
+      "2024-10-23 21:12:19,797, data_manager.py, 73, INFO, Processing ticker ACN\n",
+      "2024-10-23 21:12:19,799, data_manager.py, 108, INFO, Getting stock price data for ACN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:19,799, data_manager.py, 108, INFO, Getting stock price data for ACN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:20,144, data_manager.py, 82, INFO, Saving data for ACN by year\n",
+      "2024-10-23 21:12:20,144, data_manager.py, 82, INFO, Saving data for ACN by year\n",
+      "2024-10-23 21:12:21,640, data_manager.py, 73, INFO, Processing ticker ADBE\n",
+      "2024-10-23 21:12:21,640, data_manager.py, 73, INFO, Processing ticker ADBE\n",
+      "2024-10-23 21:12:21,642, data_manager.py, 108, INFO, Getting stock price data for ADBE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:21,642, data_manager.py, 108, INFO, Getting stock price data for ADBE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:21,965, data_manager.py, 82, INFO, Saving data for ADBE by year\n",
+      "2024-10-23 21:12:21,965, data_manager.py, 82, INFO, Saving data for ADBE by year\n",
+      "2024-10-23 21:12:23,467, data_manager.py, 73, INFO, Processing ticker AMD\n",
+      "2024-10-23 21:12:23,467, data_manager.py, 73, INFO, Processing ticker AMD\n",
+      "2024-10-23 21:12:23,469, data_manager.py, 108, INFO, Getting stock price data for AMD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:23,469, data_manager.py, 108, INFO, Getting stock price data for AMD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:23,743, data_manager.py, 82, INFO, Saving data for AMD by year\n",
+      "2024-10-23 21:12:23,743, data_manager.py, 82, INFO, Saving data for AMD by year\n",
+      "2024-10-23 21:12:25,023, data_manager.py, 73, INFO, Processing ticker AES\n",
+      "2024-10-23 21:12:25,023, data_manager.py, 73, INFO, Processing ticker AES\n",
+      "2024-10-23 21:12:25,026, data_manager.py, 108, INFO, Getting stock price data for AES from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:25,026, data_manager.py, 108, INFO, Getting stock price data for AES from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:25,382, data_manager.py, 82, INFO, Saving data for AES by year\n",
+      "2024-10-23 21:12:25,382, data_manager.py, 82, INFO, Saving data for AES by year\n",
+      "2024-10-23 21:12:26,769, data_manager.py, 73, INFO, Processing ticker AFL\n",
+      "2024-10-23 21:12:26,769, data_manager.py, 73, INFO, Processing ticker AFL\n",
+      "2024-10-23 21:12:26,771, data_manager.py, 108, INFO, Getting stock price data for AFL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:26,771, data_manager.py, 108, INFO, Getting stock price data for AFL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:27,239, data_manager.py, 82, INFO, Saving data for AFL by year\n",
+      "2024-10-23 21:12:27,239, data_manager.py, 82, INFO, Saving data for AFL by year\n",
+      "2024-10-23 21:12:28,585, data_manager.py, 73, INFO, Processing ticker A\n",
+      "2024-10-23 21:12:28,585, data_manager.py, 73, INFO, Processing ticker A\n",
+      "2024-10-23 21:12:28,587, data_manager.py, 108, INFO, Getting stock price data for A from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:28,587, data_manager.py, 108, INFO, Getting stock price data for A from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:28,924, data_manager.py, 82, INFO, Saving data for A by year\n",
+      "2024-10-23 21:12:28,924, data_manager.py, 82, INFO, Saving data for A by year\n",
+      "2024-10-23 21:12:30,359, data_manager.py, 73, INFO, Processing ticker APD\n",
+      "2024-10-23 21:12:30,359, data_manager.py, 73, INFO, Processing ticker APD\n",
+      "2024-10-23 21:12:30,361, data_manager.py, 108, INFO, Getting stock price data for APD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:30,361, data_manager.py, 108, INFO, Getting stock price data for APD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:30,697, data_manager.py, 82, INFO, Saving data for APD by year\n",
+      "2024-10-23 21:12:30,697, data_manager.py, 82, INFO, Saving data for APD by year\n",
+      "2024-10-23 21:12:32,004, data_manager.py, 73, INFO, Processing ticker ABNB\n",
+      "2024-10-23 21:12:32,004, data_manager.py, 73, INFO, Processing ticker ABNB\n",
+      "2024-10-23 21:12:32,006, data_manager.py, 108, INFO, Getting stock price data for ABNB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:32,006, data_manager.py, 108, INFO, Getting stock price data for ABNB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:32,108, data_manager.py, 82, INFO, Saving data for ABNB by year\n",
+      "2024-10-23 21:12:32,108, data_manager.py, 82, INFO, Saving data for ABNB by year\n",
+      "2024-10-23 21:12:32,422, data_manager.py, 73, INFO, Processing ticker AKAM\n",
+      "2024-10-23 21:12:32,422, data_manager.py, 73, INFO, Processing ticker AKAM\n",
+      "2024-10-23 21:12:32,426, data_manager.py, 108, INFO, Getting stock price data for AKAM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:32,426, data_manager.py, 108, INFO, Getting stock price data for AKAM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:32,583, data_manager.py, 82, INFO, Saving data for AKAM by year\n",
+      "2024-10-23 21:12:32,583, data_manager.py, 82, INFO, Saving data for AKAM by year\n",
+      "2024-10-23 21:12:34,022, data_manager.py, 73, INFO, Processing ticker ALB\n",
+      "2024-10-23 21:12:34,022, data_manager.py, 73, INFO, Processing ticker ALB\n",
+      "2024-10-23 21:12:34,024, data_manager.py, 108, INFO, Getting stock price data for ALB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:34,024, data_manager.py, 108, INFO, Getting stock price data for ALB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:34,385, data_manager.py, 82, INFO, Saving data for ALB by year\n",
+      "2024-10-23 21:12:34,385, data_manager.py, 82, INFO, Saving data for ALB by year\n",
+      "2024-10-23 21:12:35,885, data_manager.py, 73, INFO, Processing ticker ARE\n",
+      "2024-10-23 21:12:35,885, data_manager.py, 73, INFO, Processing ticker ARE\n",
+      "2024-10-23 21:12:35,887, data_manager.py, 108, INFO, Getting stock price data for ARE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:35,887, data_manager.py, 108, INFO, Getting stock price data for ARE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:36,178, data_manager.py, 82, INFO, Saving data for ARE by year\n",
+      "2024-10-23 21:12:36,178, data_manager.py, 82, INFO, Saving data for ARE by year\n",
+      "2024-10-23 21:12:37,643, data_manager.py, 73, INFO, Processing ticker ALGN\n",
+      "2024-10-23 21:12:37,643, data_manager.py, 73, INFO, Processing ticker ALGN\n",
+      "2024-10-23 21:12:37,646, data_manager.py, 108, INFO, Getting stock price data for ALGN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:37,646, data_manager.py, 108, INFO, Getting stock price data for ALGN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:38,058, data_manager.py, 82, INFO, Saving data for ALGN by year\n",
+      "2024-10-23 21:12:38,058, data_manager.py, 82, INFO, Saving data for ALGN by year\n",
+      "2024-10-23 21:12:39,375, data_manager.py, 73, INFO, Processing ticker ALLE\n",
+      "2024-10-23 21:12:39,375, data_manager.py, 73, INFO, Processing ticker ALLE\n",
+      "2024-10-23 21:12:39,377, data_manager.py, 108, INFO, Getting stock price data for ALLE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:39,377, data_manager.py, 108, INFO, Getting stock price data for ALLE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:39,637, data_manager.py, 82, INFO, Saving data for ALLE by year\n",
+      "2024-10-23 21:12:39,637, data_manager.py, 82, INFO, Saving data for ALLE by year\n",
+      "2024-10-23 21:12:40,460, data_manager.py, 73, INFO, Processing ticker LNT\n",
+      "2024-10-23 21:12:40,460, data_manager.py, 73, INFO, Processing ticker LNT\n",
+      "2024-10-23 21:12:40,462, data_manager.py, 108, INFO, Getting stock price data for LNT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:40,462, data_manager.py, 108, INFO, Getting stock price data for LNT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:40,878, data_manager.py, 82, INFO, Saving data for LNT by year\n",
+      "2024-10-23 21:12:40,878, data_manager.py, 82, INFO, Saving data for LNT by year\n",
+      "2024-10-23 21:12:42,349, data_manager.py, 73, INFO, Processing ticker ALL\n",
+      "2024-10-23 21:12:42,349, data_manager.py, 73, INFO, Processing ticker ALL\n",
+      "2024-10-23 21:12:42,352, data_manager.py, 108, INFO, Getting stock price data for ALL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:42,352, data_manager.py, 108, INFO, Getting stock price data for ALL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:42,704, data_manager.py, 82, INFO, Saving data for ALL by year\n",
+      "2024-10-23 21:12:42,704, data_manager.py, 82, INFO, Saving data for ALL by year\n",
+      "2024-10-23 21:12:44,025, data_manager.py, 73, INFO, Processing ticker GOOGL\n",
+      "2024-10-23 21:12:44,025, data_manager.py, 73, INFO, Processing ticker GOOGL\n",
+      "2024-10-23 21:12:44,027, data_manager.py, 108, INFO, Getting stock price data for GOOGL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:44,027, data_manager.py, 108, INFO, Getting stock price data for GOOGL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:44,467, data_manager.py, 82, INFO, Saving data for GOOGL by year\n",
+      "2024-10-23 21:12:44,467, data_manager.py, 82, INFO, Saving data for GOOGL by year\n",
+      "2024-10-23 21:12:45,753, data_manager.py, 73, INFO, Processing ticker GOOG\n",
+      "2024-10-23 21:12:45,753, data_manager.py, 73, INFO, Processing ticker GOOG\n",
+      "2024-10-23 21:12:45,755, data_manager.py, 108, INFO, Getting stock price data for GOOG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:45,755, data_manager.py, 108, INFO, Getting stock price data for GOOG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:46,258, data_manager.py, 82, INFO, Saving data for GOOG by year\n",
+      "2024-10-23 21:12:46,258, data_manager.py, 82, INFO, Saving data for GOOG by year\n",
+      "2024-10-23 21:12:47,477, data_manager.py, 73, INFO, Processing ticker MO\n",
+      "2024-10-23 21:12:47,477, data_manager.py, 73, INFO, Processing ticker MO\n",
+      "2024-10-23 21:12:47,479, data_manager.py, 108, INFO, Getting stock price data for MO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:47,479, data_manager.py, 108, INFO, Getting stock price data for MO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:47,880, data_manager.py, 82, INFO, Saving data for MO by year\n",
+      "2024-10-23 21:12:47,880, data_manager.py, 82, INFO, Saving data for MO by year\n",
+      "2024-10-23 21:12:49,060, data_manager.py, 73, INFO, Processing ticker AMZN\n",
+      "2024-10-23 21:12:49,060, data_manager.py, 73, INFO, Processing ticker AMZN\n",
+      "2024-10-23 21:12:49,061, data_manager.py, 108, INFO, Getting stock price data for AMZN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:49,061, data_manager.py, 108, INFO, Getting stock price data for AMZN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:49,402, data_manager.py, 82, INFO, Saving data for AMZN by year\n",
+      "2024-10-23 21:12:49,402, data_manager.py, 82, INFO, Saving data for AMZN by year\n",
+      "2024-10-23 21:12:50,591, data_manager.py, 73, INFO, Processing ticker AMCR\n",
+      "2024-10-23 21:12:50,591, data_manager.py, 73, INFO, Processing ticker AMCR\n",
+      "2024-10-23 21:12:50,593, data_manager.py, 108, INFO, Getting stock price data for AMCR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:50,593, data_manager.py, 108, INFO, Getting stock price data for AMCR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:50,786, data_manager.py, 82, INFO, Saving data for AMCR by year\n",
+      "2024-10-23 21:12:50,786, data_manager.py, 82, INFO, Saving data for AMCR by year\n",
+      "2024-10-23 21:12:51,479, data_manager.py, 73, INFO, Processing ticker AEE\n",
+      "2024-10-23 21:12:51,479, data_manager.py, 73, INFO, Processing ticker AEE\n",
+      "2024-10-23 21:12:51,481, data_manager.py, 108, INFO, Getting stock price data for AEE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:51,481, data_manager.py, 108, INFO, Getting stock price data for AEE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:51,892, data_manager.py, 82, INFO, Saving data for AEE by year\n",
+      "2024-10-23 21:12:51,892, data_manager.py, 82, INFO, Saving data for AEE by year\n",
+      "2024-10-23 21:12:53,076, data_manager.py, 73, INFO, Processing ticker AAL\n",
+      "2024-10-23 21:12:53,076, data_manager.py, 73, INFO, Processing ticker AAL\n",
+      "2024-10-23 21:12:53,077, data_manager.py, 108, INFO, Getting stock price data for AAL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:53,077, data_manager.py, 108, INFO, Getting stock price data for AAL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:14,352, data_manager.py, 82, INFO, Saving data for AAL by year\n",
+      "2024-10-23 21:13:14,352, data_manager.py, 82, INFO, Saving data for AAL by year\n",
+      "2024-10-23 21:12:54,418, data_manager.py, 73, INFO, Processing ticker AEP\n",
+      "2024-10-23 21:12:54,418, data_manager.py, 73, INFO, Processing ticker AEP\n",
+      "2024-10-23 21:12:54,420, data_manager.py, 108, INFO, Getting stock price data for AEP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:54,420, data_manager.py, 108, INFO, Getting stock price data for AEP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:54,820, data_manager.py, 82, INFO, Saving data for AEP by year\n",
+      "2024-10-23 21:12:54,820, data_manager.py, 82, INFO, Saving data for AEP by year\n",
+      "2024-10-23 21:12:56,020, data_manager.py, 73, INFO, Processing ticker AXP\n",
+      "2024-10-23 21:12:56,020, data_manager.py, 73, INFO, Processing ticker AXP\n",
+      "2024-10-23 21:12:56,021, data_manager.py, 108, INFO, Getting stock price data for AXP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:56,021, data_manager.py, 108, INFO, Getting stock price data for AXP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:56,431, data_manager.py, 82, INFO, Saving data for AXP by year\n",
+      "2024-10-23 21:12:56,431, data_manager.py, 82, INFO, Saving data for AXP by year\n",
+      "2024-10-23 21:12:57,642, data_manager.py, 73, INFO, Processing ticker AIG\n",
+      "2024-10-23 21:12:57,642, data_manager.py, 73, INFO, Processing ticker AIG\n",
+      "2024-10-23 21:12:57,645, data_manager.py, 108, INFO, Getting stock price data for AIG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:57,645, data_manager.py, 108, INFO, Getting stock price data for AIG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:58,013, data_manager.py, 82, INFO, Saving data for AIG by year\n",
+      "2024-10-23 21:12:58,013, data_manager.py, 82, INFO, Saving data for AIG by year\n",
+      "2024-10-23 21:12:59,372, data_manager.py, 73, INFO, Processing ticker AMT\n",
+      "2024-10-23 21:12:59,372, data_manager.py, 73, INFO, Processing ticker AMT\n",
+      "2024-10-23 21:12:59,374, data_manager.py, 108, INFO, Getting stock price data for AMT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:12:59,374, data_manager.py, 108, INFO, Getting stock price data for AMT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:12:59,695, data_manager.py, 82, INFO, Saving data for AMT by year\n",
+      "2024-10-23 21:12:59,695, data_manager.py, 82, INFO, Saving data for AMT by year\n",
+      "2024-10-23 21:13:01,108, data_manager.py, 73, INFO, Processing ticker AWK\n",
+      "2024-10-23 21:13:01,108, data_manager.py, 73, INFO, Processing ticker AWK\n",
+      "2024-10-23 21:13:01,109, data_manager.py, 108, INFO, Getting stock price data for AWK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:01,109, data_manager.py, 108, INFO, Getting stock price data for AWK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:01,365, data_manager.py, 82, INFO, Saving data for AWK by year\n",
+      "2024-10-23 21:13:01,365, data_manager.py, 82, INFO, Saving data for AWK by year\n",
+      "2024-10-23 21:13:02,305, data_manager.py, 73, INFO, Processing ticker AMP\n",
+      "2024-10-23 21:13:02,305, data_manager.py, 73, INFO, Processing ticker AMP\n",
+      "2024-10-23 21:13:02,307, data_manager.py, 108, INFO, Getting stock price data for AMP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:02,307, data_manager.py, 108, INFO, Getting stock price data for AMP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:02,563, data_manager.py, 82, INFO, Saving data for AMP by year\n",
+      "2024-10-23 21:13:02,563, data_manager.py, 82, INFO, Saving data for AMP by year\n",
+      "2024-10-23 21:13:03,545, data_manager.py, 73, INFO, Processing ticker AME\n",
+      "2024-10-23 21:13:03,545, data_manager.py, 73, INFO, Processing ticker AME\n",
+      "2024-10-23 21:13:03,547, data_manager.py, 108, INFO, Getting stock price data for AME from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:03,547, data_manager.py, 108, INFO, Getting stock price data for AME from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:03,909, data_manager.py, 82, INFO, Saving data for AME by year\n",
+      "2024-10-23 21:13:03,909, data_manager.py, 82, INFO, Saving data for AME by year\n",
+      "2024-10-23 21:13:05,198, data_manager.py, 73, INFO, Processing ticker AMGN\n",
+      "2024-10-23 21:13:05,198, data_manager.py, 73, INFO, Processing ticker AMGN\n",
+      "2024-10-23 21:13:05,201, data_manager.py, 108, INFO, Getting stock price data for AMGN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:05,201, data_manager.py, 108, INFO, Getting stock price data for AMGN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:05,466, data_manager.py, 82, INFO, Saving data for AMGN by year\n",
+      "2024-10-23 21:13:05,466, data_manager.py, 82, INFO, Saving data for AMGN by year\n",
+      "2024-10-23 21:13:06,785, data_manager.py, 73, INFO, Processing ticker APH\n",
+      "2024-10-23 21:13:06,785, data_manager.py, 73, INFO, Processing ticker APH\n",
+      "2024-10-23 21:13:06,787, data_manager.py, 108, INFO, Getting stock price data for APH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:06,787, data_manager.py, 108, INFO, Getting stock price data for APH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:07,056, data_manager.py, 82, INFO, Saving data for APH by year\n",
+      "2024-10-23 21:13:07,056, data_manager.py, 82, INFO, Saving data for APH by year\n",
+      "2024-10-23 21:13:08,434, data_manager.py, 73, INFO, Processing ticker ADI\n",
+      "2024-10-23 21:13:08,434, data_manager.py, 73, INFO, Processing ticker ADI\n",
+      "2024-10-23 21:13:08,436, data_manager.py, 108, INFO, Getting stock price data for ADI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:08,436, data_manager.py, 108, INFO, Getting stock price data for ADI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:08,796, data_manager.py, 82, INFO, Saving data for ADI by year\n",
+      "2024-10-23 21:13:08,796, data_manager.py, 82, INFO, Saving data for ADI by year\n",
+      "2024-10-23 21:13:10,131, data_manager.py, 73, INFO, Processing ticker ANSS\n",
+      "2024-10-23 21:13:10,131, data_manager.py, 73, INFO, Processing ticker ANSS\n",
+      "2024-10-23 21:13:10,132, data_manager.py, 108, INFO, Getting stock price data for ANSS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:10,132, data_manager.py, 108, INFO, Getting stock price data for ANSS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:10,354, data_manager.py, 82, INFO, Saving data for ANSS by year\n",
+      "2024-10-23 21:13:10,354, data_manager.py, 82, INFO, Saving data for ANSS by year\n",
+      "2024-10-23 21:13:11,683, data_manager.py, 73, INFO, Processing ticker AON\n",
+      "2024-10-23 21:13:11,683, data_manager.py, 73, INFO, Processing ticker AON\n",
+      "2024-10-23 21:13:11,685, data_manager.py, 108, INFO, Getting stock price data for AON from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:11,685, data_manager.py, 108, INFO, Getting stock price data for AON from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:11,954, data_manager.py, 82, INFO, Saving data for AON by year\n",
+      "2024-10-23 21:13:11,954, data_manager.py, 82, INFO, Saving data for AON by year\n",
+      "2024-10-23 21:13:34,390, data_manager.py, 73, INFO, Processing ticker APA\n",
+      "2024-10-23 21:13:34,390, data_manager.py, 73, INFO, Processing ticker APA\n",
+      "2024-10-23 21:13:34,392, data_manager.py, 108, INFO, Getting stock price data for APA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:34,392, data_manager.py, 108, INFO, Getting stock price data for APA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:13,676, data_manager.py, 82, INFO, Saving data for APA by year\n",
+      "2024-10-23 21:13:13,676, data_manager.py, 82, INFO, Saving data for APA by year\n",
+      "2024-10-23 21:13:14,995, data_manager.py, 73, INFO, Processing ticker AAPL\n",
+      "2024-10-23 21:13:14,995, data_manager.py, 73, INFO, Processing ticker AAPL\n",
+      "2024-10-23 21:13:14,997, data_manager.py, 108, INFO, Getting stock price data for AAPL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:14,997, data_manager.py, 108, INFO, Getting stock price data for AAPL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:15,311, data_manager.py, 82, INFO, Saving data for AAPL by year\n",
+      "2024-10-23 21:13:15,311, data_manager.py, 82, INFO, Saving data for AAPL by year\n",
+      "2024-10-23 21:13:16,613, data_manager.py, 73, INFO, Processing ticker AMAT\n",
+      "2024-10-23 21:13:16,613, data_manager.py, 73, INFO, Processing ticker AMAT\n",
+      "2024-10-23 21:13:16,615, data_manager.py, 108, INFO, Getting stock price data for AMAT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:16,615, data_manager.py, 108, INFO, Getting stock price data for AMAT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:16,959, data_manager.py, 82, INFO, Saving data for AMAT by year\n",
+      "2024-10-23 21:13:16,959, data_manager.py, 82, INFO, Saving data for AMAT by year\n",
+      "2024-10-23 21:13:18,159, data_manager.py, 73, INFO, Processing ticker APTV\n",
+      "2024-10-23 21:13:18,159, data_manager.py, 73, INFO, Processing ticker APTV\n",
+      "2024-10-23 21:13:18,161, data_manager.py, 108, INFO, Getting stock price data for APTV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:18,161, data_manager.py, 108, INFO, Getting stock price data for APTV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:18,422, data_manager.py, 82, INFO, Saving data for APTV by year\n",
+      "2024-10-23 21:13:18,422, data_manager.py, 82, INFO, Saving data for APTV by year\n",
+      "2024-10-23 21:13:18,990, data_manager.py, 73, INFO, Processing ticker ACGL\n",
+      "2024-10-23 21:13:18,990, data_manager.py, 73, INFO, Processing ticker ACGL\n",
+      "2024-10-23 21:13:18,992, data_manager.py, 108, INFO, Getting stock price data for ACGL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:18,992, data_manager.py, 108, INFO, Getting stock price data for ACGL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:19,215, data_manager.py, 82, INFO, Saving data for ACGL by year\n",
+      "2024-10-23 21:13:19,215, data_manager.py, 82, INFO, Saving data for ACGL by year\n",
+      "2024-10-23 21:13:20,511, data_manager.py, 73, INFO, Processing ticker ADM\n",
+      "2024-10-23 21:13:20,511, data_manager.py, 73, INFO, Processing ticker ADM\n",
+      "2024-10-23 21:13:20,512, data_manager.py, 108, INFO, Getting stock price data for ADM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:20,512, data_manager.py, 108, INFO, Getting stock price data for ADM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:20,775, data_manager.py, 82, INFO, Saving data for ADM by year\n",
+      "2024-10-23 21:13:20,775, data_manager.py, 82, INFO, Saving data for ADM by year\n",
+      "2024-10-23 21:13:22,023, data_manager.py, 73, INFO, Processing ticker ANET\n",
+      "2024-10-23 21:13:22,023, data_manager.py, 73, INFO, Processing ticker ANET\n",
+      "2024-10-23 21:13:22,025, data_manager.py, 108, INFO, Getting stock price data for ANET from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:22,025, data_manager.py, 108, INFO, Getting stock price data for ANET from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:22,172, data_manager.py, 82, INFO, Saving data for ANET by year\n",
+      "2024-10-23 21:13:22,172, data_manager.py, 82, INFO, Saving data for ANET by year\n",
+      "2024-10-23 21:13:22,646, data_manager.py, 73, INFO, Processing ticker AJG\n",
+      "2024-10-23 21:13:22,646, data_manager.py, 73, INFO, Processing ticker AJG\n",
+      "2024-10-23 21:13:22,647, data_manager.py, 108, INFO, Getting stock price data for AJG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:22,647, data_manager.py, 108, INFO, Getting stock price data for AJG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:22,982, data_manager.py, 82, INFO, Saving data for AJG by year\n",
+      "2024-10-23 21:13:22,982, data_manager.py, 82, INFO, Saving data for AJG by year\n",
+      "2024-10-23 21:13:24,216, data_manager.py, 73, INFO, Processing ticker AIZ\n",
+      "2024-10-23 21:13:24,216, data_manager.py, 73, INFO, Processing ticker AIZ\n",
+      "2024-10-23 21:13:24,218, data_manager.py, 108, INFO, Getting stock price data for AIZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:24,218, data_manager.py, 108, INFO, Getting stock price data for AIZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:24,456, data_manager.py, 82, INFO, Saving data for AIZ by year\n",
+      "2024-10-23 21:13:24,456, data_manager.py, 82, INFO, Saving data for AIZ by year\n",
+      "2024-10-23 21:13:25,534, data_manager.py, 73, INFO, Processing ticker T\n",
+      "2024-10-23 21:13:25,534, data_manager.py, 73, INFO, Processing ticker T\n",
+      "2024-10-23 21:13:25,537, data_manager.py, 108, INFO, Getting stock price data for T from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:25,537, data_manager.py, 108, INFO, Getting stock price data for T from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:25,834, data_manager.py, 82, INFO, Saving data for T by year\n",
+      "2024-10-23 21:13:25,834, data_manager.py, 82, INFO, Saving data for T by year\n",
+      "2024-10-23 21:13:27,007, data_manager.py, 73, INFO, Processing ticker ATO\n",
+      "2024-10-23 21:13:27,007, data_manager.py, 73, INFO, Processing ticker ATO\n",
+      "2024-10-23 21:13:27,008, data_manager.py, 108, INFO, Getting stock price data for ATO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:27,008, data_manager.py, 108, INFO, Getting stock price data for ATO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:27,277, data_manager.py, 82, INFO, Saving data for ATO by year\n",
+      "2024-10-23 21:13:27,277, data_manager.py, 82, INFO, Saving data for ATO by year\n",
+      "2024-10-23 21:13:28,631, data_manager.py, 73, INFO, Processing ticker ADSK\n",
+      "2024-10-23 21:13:28,631, data_manager.py, 73, INFO, Processing ticker ADSK\n",
+      "2024-10-23 21:13:28,632, data_manager.py, 108, INFO, Getting stock price data for ADSK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:28,632, data_manager.py, 108, INFO, Getting stock price data for ADSK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:28,863, data_manager.py, 82, INFO, Saving data for ADSK by year\n",
+      "2024-10-23 21:13:28,863, data_manager.py, 82, INFO, Saving data for ADSK by year\n",
+      "2024-10-23 21:13:30,057, data_manager.py, 73, INFO, Processing ticker ADP\n",
+      "2024-10-23 21:13:30,057, data_manager.py, 73, INFO, Processing ticker ADP\n",
+      "2024-10-23 21:13:30,059, data_manager.py, 108, INFO, Getting stock price data for ADP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:30,059, data_manager.py, 108, INFO, Getting stock price data for ADP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:30,337, data_manager.py, 82, INFO, Saving data for ADP by year\n",
+      "2024-10-23 21:13:30,337, data_manager.py, 82, INFO, Saving data for ADP by year\n",
+      "2024-10-23 21:13:31,593, data_manager.py, 73, INFO, Processing ticker AZO\n",
+      "2024-10-23 21:13:31,593, data_manager.py, 73, INFO, Processing ticker AZO\n",
+      "2024-10-23 21:13:31,595, data_manager.py, 108, INFO, Getting stock price data for AZO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:31,595, data_manager.py, 108, INFO, Getting stock price data for AZO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:31,786, data_manager.py, 82, INFO, Saving data for AZO by year\n",
+      "2024-10-23 21:13:31,786, data_manager.py, 82, INFO, Saving data for AZO by year\n",
+      "2024-10-23 21:13:32,966, data_manager.py, 73, INFO, Processing ticker AVB\n",
+      "2024-10-23 21:13:32,966, data_manager.py, 73, INFO, Processing ticker AVB\n",
+      "2024-10-23 21:13:32,968, data_manager.py, 108, INFO, Getting stock price data for AVB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:32,968, data_manager.py, 108, INFO, Getting stock price data for AVB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:33,284, data_manager.py, 82, INFO, Saving data for AVB by year\n",
+      "2024-10-23 21:13:33,284, data_manager.py, 82, INFO, Saving data for AVB by year\n",
+      "2024-10-23 21:13:34,642, data_manager.py, 73, INFO, Processing ticker AVY\n",
+      "2024-10-23 21:13:34,642, data_manager.py, 73, INFO, Processing ticker AVY\n",
+      "2024-10-23 21:13:34,643, data_manager.py, 108, INFO, Getting stock price data for AVY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:34,643, data_manager.py, 108, INFO, Getting stock price data for AVY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:34,900, data_manager.py, 82, INFO, Saving data for AVY by year\n",
+      "2024-10-23 21:13:34,900, data_manager.py, 82, INFO, Saving data for AVY by year\n",
+      "2024-10-23 21:13:36,165, data_manager.py, 73, INFO, Processing ticker AXON\n",
+      "2024-10-23 21:13:36,165, data_manager.py, 73, INFO, Processing ticker AXON\n",
+      "2024-10-23 21:13:36,166, data_manager.py, 108, INFO, Getting stock price data for AXON from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:36,166, data_manager.py, 108, INFO, Getting stock price data for AXON from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:36,340, data_manager.py, 82, INFO, Saving data for AXON by year\n",
+      "2024-10-23 21:13:36,340, data_manager.py, 82, INFO, Saving data for AXON by year\n",
+      "2024-10-23 21:13:37,620, data_manager.py, 73, INFO, Processing ticker BKR\n",
+      "2024-10-23 21:13:37,620, data_manager.py, 73, INFO, Processing ticker BKR\n",
+      "2024-10-23 21:13:37,624, data_manager.py, 108, INFO, Getting stock price data for BKR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:37,624, data_manager.py, 108, INFO, Getting stock price data for BKR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:37,856, data_manager.py, 82, INFO, Saving data for BKR by year\n",
+      "2024-10-23 21:13:37,856, data_manager.py, 82, INFO, Saving data for BKR by year\n",
+      "2024-10-23 21:13:39,149, data_manager.py, 73, INFO, Processing ticker BALL\n",
+      "2024-10-23 21:13:39,149, data_manager.py, 73, INFO, Processing ticker BALL\n",
+      "2024-10-23 21:13:39,151, data_manager.py, 108, INFO, Getting stock price data for BALL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:39,151, data_manager.py, 108, INFO, Getting stock price data for BALL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:39,407, data_manager.py, 82, INFO, Saving data for BALL by year\n",
+      "2024-10-23 21:13:39,407, data_manager.py, 82, INFO, Saving data for BALL by year\n",
+      "2024-10-23 21:13:40,617, data_manager.py, 73, INFO, Processing ticker BAC\n",
+      "2024-10-23 21:13:40,617, data_manager.py, 73, INFO, Processing ticker BAC\n",
+      "2024-10-23 21:13:40,618, data_manager.py, 108, INFO, Getting stock price data for BAC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:40,618, data_manager.py, 108, INFO, Getting stock price data for BAC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:40,881, data_manager.py, 82, INFO, Saving data for BAC by year\n",
+      "2024-10-23 21:13:40,881, data_manager.py, 82, INFO, Saving data for BAC by year\n",
+      "2024-10-23 21:13:42,070, data_manager.py, 73, INFO, Processing ticker BK\n",
+      "2024-10-23 21:13:42,070, data_manager.py, 73, INFO, Processing ticker BK\n",
+      "2024-10-23 21:13:42,072, data_manager.py, 108, INFO, Getting stock price data for BK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:42,072, data_manager.py, 108, INFO, Getting stock price data for BK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:42,319, data_manager.py, 82, INFO, Saving data for BK by year\n",
+      "2024-10-23 21:13:42,319, data_manager.py, 82, INFO, Saving data for BK by year\n",
+      "2024-10-23 21:13:43,530, data_manager.py, 73, INFO, Processing ticker BBWI\n",
+      "2024-10-23 21:13:43,530, data_manager.py, 73, INFO, Processing ticker BBWI\n",
+      "2024-10-23 21:13:43,531, data_manager.py, 108, INFO, Getting stock price data for BBWI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:43,531, data_manager.py, 108, INFO, Getting stock price data for BBWI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:43,961, data_manager.py, 82, INFO, Saving data for BBWI by year\n",
+      "2024-10-23 21:13:43,961, data_manager.py, 82, INFO, Saving data for BBWI by year\n",
+      "2024-10-23 21:13:45,252, data_manager.py, 73, INFO, Processing ticker BAX\n",
+      "2024-10-23 21:13:45,252, data_manager.py, 73, INFO, Processing ticker BAX\n",
+      "2024-10-23 21:13:45,253, data_manager.py, 108, INFO, Getting stock price data for BAX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:45,253, data_manager.py, 108, INFO, Getting stock price data for BAX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:45,570, data_manager.py, 82, INFO, Saving data for BAX by year\n",
+      "2024-10-23 21:13:45,570, data_manager.py, 82, INFO, Saving data for BAX by year\n",
+      "2024-10-23 21:13:46,839, data_manager.py, 73, INFO, Processing ticker BDX\n",
+      "2024-10-23 21:13:46,839, data_manager.py, 73, INFO, Processing ticker BDX\n",
+      "2024-10-23 21:13:46,841, data_manager.py, 108, INFO, Getting stock price data for BDX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:46,841, data_manager.py, 108, INFO, Getting stock price data for BDX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:47,108, data_manager.py, 82, INFO, Saving data for BDX by year\n",
+      "2024-10-23 21:13:47,108, data_manager.py, 82, INFO, Saving data for BDX by year\n",
+      "2024-10-23 21:13:48,350, data_manager.py, 73, INFO, Processing ticker BRK.B\n",
+      "2024-10-23 21:13:48,350, data_manager.py, 73, INFO, Processing ticker BRK.B\n",
+      "2024-10-23 21:13:48,352, data_manager.py, 108, INFO, Getting stock price data for BRK.B from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:48,352, data_manager.py, 108, INFO, Getting stock price data for BRK.B from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['BRK.B']: YFTzMissingError('$%ticker%: possibly delisted; No timezone found')\n",
+      "2024-10-23 21:13:49,839, data_manager.py, 82, INFO, Saving data for BRK.B by year\n",
+      "2024-10-23 21:13:49,839, data_manager.py, 82, INFO, Saving data for BRK.B by year\n",
+      "2024-10-23 21:13:49,841, data_manager.py, 100, WARNING, No data found for BRK.B\n",
+      "2024-10-23 21:13:49,841, data_manager.py, 100, WARNING, No data found for BRK.B\n",
+      "2024-10-23 21:13:49,843, data_manager.py, 73, INFO, Processing ticker BBY\n",
+      "2024-10-23 21:13:49,843, data_manager.py, 73, INFO, Processing ticker BBY\n",
+      "2024-10-23 21:13:49,844, data_manager.py, 108, INFO, Getting stock price data for BBY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:49,844, data_manager.py, 108, INFO, Getting stock price data for BBY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:50,083, data_manager.py, 82, INFO, Saving data for BBY by year\n",
+      "2024-10-23 21:13:50,083, data_manager.py, 82, INFO, Saving data for BBY by year\n",
+      "2024-10-23 21:13:51,477, data_manager.py, 73, INFO, Processing ticker BIO\n",
+      "2024-10-23 21:13:51,477, data_manager.py, 73, INFO, Processing ticker BIO\n",
+      "2024-10-23 21:13:51,479, data_manager.py, 108, INFO, Getting stock price data for BIO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:51,479, data_manager.py, 108, INFO, Getting stock price data for BIO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:51,680, data_manager.py, 82, INFO, Saving data for BIO by year\n",
+      "2024-10-23 21:13:51,680, data_manager.py, 82, INFO, Saving data for BIO by year\n",
+      "2024-10-23 21:13:52,954, data_manager.py, 73, INFO, Processing ticker TECH\n",
+      "2024-10-23 21:13:52,954, data_manager.py, 73, INFO, Processing ticker TECH\n",
+      "2024-10-23 21:13:52,955, data_manager.py, 108, INFO, Getting stock price data for TECH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:52,955, data_manager.py, 108, INFO, Getting stock price data for TECH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:53,195, data_manager.py, 82, INFO, Saving data for TECH by year\n",
+      "2024-10-23 21:13:53,195, data_manager.py, 82, INFO, Saving data for TECH by year\n",
+      "2024-10-23 21:13:54,395, data_manager.py, 73, INFO, Processing ticker BIIB\n",
+      "2024-10-23 21:13:54,395, data_manager.py, 73, INFO, Processing ticker BIIB\n",
+      "2024-10-23 21:13:54,397, data_manager.py, 108, INFO, Getting stock price data for BIIB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:54,397, data_manager.py, 108, INFO, Getting stock price data for BIIB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:54,596, data_manager.py, 82, INFO, Saving data for BIIB by year\n",
+      "2024-10-23 21:13:54,596, data_manager.py, 82, INFO, Saving data for BIIB by year\n",
+      "2024-10-23 21:13:55,840, data_manager.py, 73, INFO, Processing ticker BLK\n",
+      "2024-10-23 21:13:55,840, data_manager.py, 73, INFO, Processing ticker BLK\n",
+      "2024-10-23 21:13:55,842, data_manager.py, 108, INFO, Getting stock price data for BLK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:55,842, data_manager.py, 108, INFO, Getting stock price data for BLK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:56,070, data_manager.py, 82, INFO, Saving data for BLK by year\n",
+      "2024-10-23 21:13:56,070, data_manager.py, 82, INFO, Saving data for BLK by year\n",
+      "2024-10-23 21:13:57,461, data_manager.py, 73, INFO, Processing ticker BX\n",
+      "2024-10-23 21:13:57,461, data_manager.py, 73, INFO, Processing ticker BX\n",
+      "2024-10-23 21:13:57,463, data_manager.py, 108, INFO, Getting stock price data for BX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:13:57,463, data_manager.py, 108, INFO, Getting stock price data for BX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:57,642, data_manager.py, 82, INFO, Saving data for BX by year\n",
+      "2024-10-23 21:13:57,642, data_manager.py, 82, INFO, Saving data for BX by year\n",
+      "2024-10-23 21:14:19,538, data_manager.py, 73, INFO, Processing ticker BA\n",
+      "2024-10-23 21:14:19,538, data_manager.py, 73, INFO, Processing ticker BA\n",
+      "2024-10-23 21:14:19,539, data_manager.py, 108, INFO, Getting stock price data for BA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:19,539, data_manager.py, 108, INFO, Getting stock price data for BA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:13:58,748, data_manager.py, 82, INFO, Saving data for BA by year\n",
+      "2024-10-23 21:13:58,748, data_manager.py, 82, INFO, Saving data for BA by year\n",
+      "2024-10-23 21:14:00,019, data_manager.py, 73, INFO, Processing ticker BKNG\n",
+      "2024-10-23 21:14:00,019, data_manager.py, 73, INFO, Processing ticker BKNG\n",
+      "2024-10-23 21:14:00,020, data_manager.py, 108, INFO, Getting stock price data for BKNG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:00,020, data_manager.py, 108, INFO, Getting stock price data for BKNG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:00,247, data_manager.py, 82, INFO, Saving data for BKNG by year\n",
+      "2024-10-23 21:14:00,247, data_manager.py, 82, INFO, Saving data for BKNG by year\n",
+      "2024-10-23 21:14:01,455, data_manager.py, 73, INFO, Processing ticker BWA\n",
+      "2024-10-23 21:14:01,455, data_manager.py, 73, INFO, Processing ticker BWA\n",
+      "2024-10-23 21:14:01,458, data_manager.py, 108, INFO, Getting stock price data for BWA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:01,458, data_manager.py, 108, INFO, Getting stock price data for BWA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:02,295, data_manager.py, 82, INFO, Saving data for BWA by year\n",
+      "2024-10-23 21:14:02,295, data_manager.py, 82, INFO, Saving data for BWA by year\n",
+      "2024-10-23 21:14:03,622, data_manager.py, 73, INFO, Processing ticker BXP\n",
+      "2024-10-23 21:14:03,622, data_manager.py, 73, INFO, Processing ticker BXP\n",
+      "2024-10-23 21:14:03,623, data_manager.py, 108, INFO, Getting stock price data for BXP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:03,623, data_manager.py, 108, INFO, Getting stock price data for BXP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:04,130, data_manager.py, 82, INFO, Saving data for BXP by year\n",
+      "2024-10-23 21:14:04,130, data_manager.py, 82, INFO, Saving data for BXP by year\n",
+      "2024-10-23 21:14:05,219, data_manager.py, 73, INFO, Processing ticker BSX\n",
+      "2024-10-23 21:14:05,219, data_manager.py, 73, INFO, Processing ticker BSX\n",
+      "2024-10-23 21:14:05,222, data_manager.py, 108, INFO, Getting stock price data for BSX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:05,222, data_manager.py, 108, INFO, Getting stock price data for BSX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:05,757, data_manager.py, 82, INFO, Saving data for BSX by year\n",
+      "2024-10-23 21:14:05,757, data_manager.py, 82, INFO, Saving data for BSX by year\n",
+      "2024-10-23 21:14:07,004, data_manager.py, 73, INFO, Processing ticker BMY\n",
+      "2024-10-23 21:14:07,004, data_manager.py, 73, INFO, Processing ticker BMY\n",
+      "2024-10-23 21:14:07,006, data_manager.py, 108, INFO, Getting stock price data for BMY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:07,006, data_manager.py, 108, INFO, Getting stock price data for BMY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:07,842, data_manager.py, 82, INFO, Saving data for BMY by year\n",
+      "2024-10-23 21:14:07,842, data_manager.py, 82, INFO, Saving data for BMY by year\n",
+      "2024-10-23 21:14:08,949, data_manager.py, 73, INFO, Processing ticker AVGO\n",
+      "2024-10-23 21:14:08,949, data_manager.py, 73, INFO, Processing ticker AVGO\n",
+      "2024-10-23 21:14:08,951, data_manager.py, 108, INFO, Getting stock price data for AVGO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:08,951, data_manager.py, 108, INFO, Getting stock price data for AVGO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:09,515, data_manager.py, 82, INFO, Saving data for AVGO by year\n",
+      "2024-10-23 21:14:09,515, data_manager.py, 82, INFO, Saving data for AVGO by year\n",
+      "2024-10-23 21:14:10,402, data_manager.py, 73, INFO, Processing ticker BR\n",
+      "2024-10-23 21:14:10,402, data_manager.py, 73, INFO, Processing ticker BR\n",
+      "2024-10-23 21:14:10,403, data_manager.py, 108, INFO, Getting stock price data for BR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:10,403, data_manager.py, 108, INFO, Getting stock price data for BR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:10,797, data_manager.py, 82, INFO, Saving data for BR by year\n",
+      "2024-10-23 21:14:10,797, data_manager.py, 82, INFO, Saving data for BR by year\n",
+      "2024-10-23 21:14:11,725, data_manager.py, 73, INFO, Processing ticker BRO\n",
+      "2024-10-23 21:14:11,725, data_manager.py, 73, INFO, Processing ticker BRO\n",
+      "2024-10-23 21:14:11,727, data_manager.py, 108, INFO, Getting stock price data for BRO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:11,727, data_manager.py, 108, INFO, Getting stock price data for BRO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:12,220, data_manager.py, 82, INFO, Saving data for BRO by year\n",
+      "2024-10-23 21:14:12,220, data_manager.py, 82, INFO, Saving data for BRO by year\n",
+      "2024-10-23 21:14:34,448, data_manager.py, 73, INFO, Processing ticker BF.B\n",
+      "2024-10-23 21:14:34,448, data_manager.py, 73, INFO, Processing ticker BF.B\n",
+      "2024-10-23 21:14:34,450, data_manager.py, 108, INFO, Getting stock price data for BF.B from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:34,450, data_manager.py, 108, INFO, Getting stock price data for BF.B from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['BF.B']: YFPricesMissingError('$%ticker%: possibly delisted; No price data found  (1d 2000-01-01 -> 2024-10-23)')\n",
+      "2024-10-23 21:14:13,774, data_manager.py, 82, INFO, Saving data for BF.B by year\n",
+      "2024-10-23 21:14:13,774, data_manager.py, 82, INFO, Saving data for BF.B by year\n",
+      "2024-10-23 21:14:13,775, data_manager.py, 100, WARNING, No data found for BF.B\n",
+      "2024-10-23 21:14:13,775, data_manager.py, 100, WARNING, No data found for BF.B\n",
+      "2024-10-23 21:14:13,777, data_manager.py, 73, INFO, Processing ticker BLDR\n",
+      "2024-10-23 21:14:13,777, data_manager.py, 73, INFO, Processing ticker BLDR\n",
+      "2024-10-23 21:14:13,778, data_manager.py, 108, INFO, Getting stock price data for BLDR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:13,778, data_manager.py, 108, INFO, Getting stock price data for BLDR from 2000-01-01 to 2024-10-23\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "$BF.B: possibly delisted; No price data found  (1d 2000-01-01 -> 2024-10-23)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:14,511, data_manager.py, 82, INFO, Saving data for BLDR by year\n",
+      "2024-10-23 21:14:14,511, data_manager.py, 82, INFO, Saving data for BLDR by year\n",
+      "2024-10-23 21:14:15,621, data_manager.py, 73, INFO, Processing ticker BG\n",
+      "2024-10-23 21:14:15,621, data_manager.py, 73, INFO, Processing ticker BG\n",
+      "2024-10-23 21:14:15,623, data_manager.py, 108, INFO, Getting stock price data for BG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:15,623, data_manager.py, 108, INFO, Getting stock price data for BG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:16,496, data_manager.py, 82, INFO, Saving data for BG by year\n",
+      "2024-10-23 21:14:16,496, data_manager.py, 82, INFO, Saving data for BG by year\n",
+      "2024-10-23 21:14:17,900, data_manager.py, 73, INFO, Processing ticker CDNS\n",
+      "2024-10-23 21:14:17,900, data_manager.py, 73, INFO, Processing ticker CDNS\n",
+      "2024-10-23 21:14:17,902, data_manager.py, 108, INFO, Getting stock price data for CDNS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:17,902, data_manager.py, 108, INFO, Getting stock price data for CDNS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:19,762, data_manager.py, 82, INFO, Saving data for CDNS by year\n",
+      "2024-10-23 21:14:19,762, data_manager.py, 82, INFO, Saving data for CDNS by year\n",
+      "2024-10-23 21:14:20,973, data_manager.py, 73, INFO, Processing ticker CZR\n",
+      "2024-10-23 21:14:20,973, data_manager.py, 73, INFO, Processing ticker CZR\n",
+      "2024-10-23 21:14:20,974, data_manager.py, 108, INFO, Getting stock price data for CZR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:20,974, data_manager.py, 108, INFO, Getting stock price data for CZR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:21,284, data_manager.py, 82, INFO, Saving data for CZR by year\n",
+      "2024-10-23 21:14:21,284, data_manager.py, 82, INFO, Saving data for CZR by year\n",
+      "2024-10-23 21:14:21,822, data_manager.py, 73, INFO, Processing ticker CPT\n",
+      "2024-10-23 21:14:21,822, data_manager.py, 73, INFO, Processing ticker CPT\n",
+      "2024-10-23 21:14:21,824, data_manager.py, 108, INFO, Getting stock price data for CPT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:21,824, data_manager.py, 108, INFO, Getting stock price data for CPT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:23,352, data_manager.py, 82, INFO, Saving data for CPT by year\n",
+      "2024-10-23 21:14:23,352, data_manager.py, 82, INFO, Saving data for CPT by year\n",
+      "2024-10-23 21:14:24,676, data_manager.py, 73, INFO, Processing ticker CPB\n",
+      "2024-10-23 21:14:24,676, data_manager.py, 73, INFO, Processing ticker CPB\n",
+      "2024-10-23 21:14:24,678, data_manager.py, 108, INFO, Getting stock price data for CPB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:24,678, data_manager.py, 108, INFO, Getting stock price data for CPB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:25,326, data_manager.py, 82, INFO, Saving data for CPB by year\n",
+      "2024-10-23 21:14:25,326, data_manager.py, 82, INFO, Saving data for CPB by year\n",
+      "2024-10-23 21:14:26,613, data_manager.py, 73, INFO, Processing ticker COF\n",
+      "2024-10-23 21:14:26,613, data_manager.py, 73, INFO, Processing ticker COF\n",
+      "2024-10-23 21:14:26,614, data_manager.py, 108, INFO, Getting stock price data for COF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:26,614, data_manager.py, 108, INFO, Getting stock price data for COF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:27,278, data_manager.py, 82, INFO, Saving data for COF by year\n",
+      "2024-10-23 21:14:27,278, data_manager.py, 82, INFO, Saving data for COF by year\n",
+      "2024-10-23 21:14:49,512, data_manager.py, 73, INFO, Processing ticker CAH\n",
+      "2024-10-23 21:14:49,512, data_manager.py, 73, INFO, Processing ticker CAH\n",
+      "2024-10-23 21:14:49,514, data_manager.py, 108, INFO, Getting stock price data for CAH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:49,514, data_manager.py, 108, INFO, Getting stock price data for CAH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:29,999, data_manager.py, 82, INFO, Saving data for CAH by year\n",
+      "2024-10-23 21:14:29,999, data_manager.py, 82, INFO, Saving data for CAH by year\n",
+      "2024-10-23 21:14:31,307, data_manager.py, 73, INFO, Processing ticker KMX\n",
+      "2024-10-23 21:14:31,307, data_manager.py, 73, INFO, Processing ticker KMX\n",
+      "2024-10-23 21:14:31,309, data_manager.py, 108, INFO, Getting stock price data for KMX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:31,309, data_manager.py, 108, INFO, Getting stock price data for KMX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:31,940, data_manager.py, 82, INFO, Saving data for KMX by year\n",
+      "2024-10-23 21:14:31,940, data_manager.py, 82, INFO, Saving data for KMX by year\n",
+      "2024-10-23 21:14:33,192, data_manager.py, 73, INFO, Processing ticker CCL\n",
+      "2024-10-23 21:14:33,192, data_manager.py, 73, INFO, Processing ticker CCL\n",
+      "2024-10-23 21:14:33,194, data_manager.py, 108, INFO, Getting stock price data for CCL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:33,194, data_manager.py, 108, INFO, Getting stock price data for CCL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:55,236, data_manager.py, 82, INFO, Saving data for CCL by year\n",
+      "2024-10-23 21:14:55,236, data_manager.py, 82, INFO, Saving data for CCL by year\n",
+      "2024-10-23 21:14:56,660, data_manager.py, 73, INFO, Processing ticker CARR\n",
+      "2024-10-23 21:14:56,660, data_manager.py, 73, INFO, Processing ticker CARR\n",
+      "2024-10-23 21:14:56,661, data_manager.py, 108, INFO, Getting stock price data for CARR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:56,661, data_manager.py, 108, INFO, Getting stock price data for CARR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:56,851, data_manager.py, 82, INFO, Saving data for CARR by year\n",
+      "2024-10-23 21:14:56,851, data_manager.py, 82, INFO, Saving data for CARR by year\n",
+      "2024-10-23 21:14:57,097, data_manager.py, 73, INFO, Processing ticker CTLT\n",
+      "2024-10-23 21:14:57,097, data_manager.py, 73, INFO, Processing ticker CTLT\n",
+      "2024-10-23 21:14:57,099, data_manager.py, 108, INFO, Getting stock price data for CTLT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:57,099, data_manager.py, 108, INFO, Getting stock price data for CTLT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:57,386, data_manager.py, 82, INFO, Saving data for CTLT by year\n",
+      "2024-10-23 21:14:57,386, data_manager.py, 82, INFO, Saving data for CTLT by year\n",
+      "2024-10-23 21:14:57,943, data_manager.py, 73, INFO, Processing ticker CAT\n",
+      "2024-10-23 21:14:57,943, data_manager.py, 73, INFO, Processing ticker CAT\n",
+      "2024-10-23 21:14:57,944, data_manager.py, 108, INFO, Getting stock price data for CAT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:57,944, data_manager.py, 108, INFO, Getting stock price data for CAT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:59,007, data_manager.py, 82, INFO, Saving data for CAT by year\n",
+      "2024-10-23 21:14:59,007, data_manager.py, 82, INFO, Saving data for CAT by year\n",
+      "2024-10-23 21:15:00,250, data_manager.py, 73, INFO, Processing ticker CBOE\n",
+      "2024-10-23 21:15:00,250, data_manager.py, 73, INFO, Processing ticker CBOE\n",
+      "2024-10-23 21:15:00,254, data_manager.py, 108, INFO, Getting stock price data for CBOE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:00,254, data_manager.py, 108, INFO, Getting stock price data for CBOE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:01,070, data_manager.py, 82, INFO, Saving data for CBOE by year\n",
+      "2024-10-23 21:15:01,070, data_manager.py, 82, INFO, Saving data for CBOE by year\n",
+      "2024-10-23 21:15:01,843, data_manager.py, 73, INFO, Processing ticker CBRE\n",
+      "2024-10-23 21:15:01,843, data_manager.py, 73, INFO, Processing ticker CBRE\n",
+      "2024-10-23 21:15:01,844, data_manager.py, 108, INFO, Getting stock price data for CBRE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:01,844, data_manager.py, 108, INFO, Getting stock price data for CBRE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:02,248, data_manager.py, 82, INFO, Saving data for CBRE by year\n",
+      "2024-10-23 21:15:02,248, data_manager.py, 82, INFO, Saving data for CBRE by year\n",
+      "2024-10-23 21:15:03,210, data_manager.py, 73, INFO, Processing ticker CDW\n",
+      "2024-10-23 21:15:03,210, data_manager.py, 73, INFO, Processing ticker CDW\n",
+      "2024-10-23 21:15:03,211, data_manager.py, 108, INFO, Getting stock price data for CDW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:03,211, data_manager.py, 108, INFO, Getting stock price data for CDW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:03,742, data_manager.py, 82, INFO, Saving data for CDW by year\n",
+      "2024-10-23 21:15:03,742, data_manager.py, 82, INFO, Saving data for CDW by year\n",
+      "2024-10-23 21:15:04,504, data_manager.py, 73, INFO, Processing ticker CE\n",
+      "2024-10-23 21:15:04,504, data_manager.py, 73, INFO, Processing ticker CE\n",
+      "2024-10-23 21:15:04,506, data_manager.py, 108, INFO, Getting stock price data for CE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:04,506, data_manager.py, 108, INFO, Getting stock price data for CE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:04,917, data_manager.py, 82, INFO, Saving data for CE by year\n",
+      "2024-10-23 21:15:04,917, data_manager.py, 82, INFO, Saving data for CE by year\n",
+      "2024-10-23 21:15:05,948, data_manager.py, 73, INFO, Processing ticker COR\n",
+      "2024-10-23 21:15:05,948, data_manager.py, 73, INFO, Processing ticker COR\n",
+      "2024-10-23 21:15:05,950, data_manager.py, 108, INFO, Getting stock price data for COR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:05,950, data_manager.py, 108, INFO, Getting stock price data for COR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:06,311, data_manager.py, 82, INFO, Saving data for COR by year\n",
+      "2024-10-23 21:15:06,311, data_manager.py, 82, INFO, Saving data for COR by year\n",
+      "2024-10-23 21:15:07,516, data_manager.py, 73, INFO, Processing ticker CNC\n",
+      "2024-10-23 21:15:07,516, data_manager.py, 73, INFO, Processing ticker CNC\n",
+      "2024-10-23 21:15:07,518, data_manager.py, 108, INFO, Getting stock price data for CNC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:07,518, data_manager.py, 108, INFO, Getting stock price data for CNC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:07,853, data_manager.py, 82, INFO, Saving data for CNC by year\n",
+      "2024-10-23 21:15:07,853, data_manager.py, 82, INFO, Saving data for CNC by year\n",
+      "2024-10-23 21:15:09,147, data_manager.py, 73, INFO, Processing ticker CNP\n",
+      "2024-10-23 21:15:09,147, data_manager.py, 73, INFO, Processing ticker CNP\n",
+      "2024-10-23 21:15:09,149, data_manager.py, 108, INFO, Getting stock price data for CNP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:09,149, data_manager.py, 108, INFO, Getting stock price data for CNP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:09,481, data_manager.py, 82, INFO, Saving data for CNP by year\n",
+      "2024-10-23 21:15:09,481, data_manager.py, 82, INFO, Saving data for CNP by year\n",
+      "2024-10-23 21:14:49,735, data_manager.py, 73, INFO, Processing ticker CF\n",
+      "2024-10-23 21:14:49,735, data_manager.py, 73, INFO, Processing ticker CF\n",
+      "2024-10-23 21:14:49,736, data_manager.py, 108, INFO, Getting stock price data for CF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:49,736, data_manager.py, 108, INFO, Getting stock price data for CF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:50,037, data_manager.py, 82, INFO, Saving data for CF by year\n",
+      "2024-10-23 21:14:50,037, data_manager.py, 82, INFO, Saving data for CF by year\n",
+      "2024-10-23 21:14:51,010, data_manager.py, 73, INFO, Processing ticker CHRW\n",
+      "2024-10-23 21:14:51,010, data_manager.py, 73, INFO, Processing ticker CHRW\n",
+      "2024-10-23 21:14:51,011, data_manager.py, 108, INFO, Getting stock price data for CHRW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:51,011, data_manager.py, 108, INFO, Getting stock price data for CHRW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:51,287, data_manager.py, 82, INFO, Saving data for CHRW by year\n",
+      "2024-10-23 21:14:51,287, data_manager.py, 82, INFO, Saving data for CHRW by year\n",
+      "2024-10-23 21:14:52,695, data_manager.py, 73, INFO, Processing ticker CRL\n",
+      "2024-10-23 21:14:52,695, data_manager.py, 73, INFO, Processing ticker CRL\n",
+      "2024-10-23 21:14:52,698, data_manager.py, 108, INFO, Getting stock price data for CRL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:52,698, data_manager.py, 108, INFO, Getting stock price data for CRL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:53,013, data_manager.py, 82, INFO, Saving data for CRL by year\n",
+      "2024-10-23 21:14:53,013, data_manager.py, 82, INFO, Saving data for CRL by year\n",
+      "2024-10-23 21:14:54,375, data_manager.py, 73, INFO, Processing ticker SCHW\n",
+      "2024-10-23 21:14:54,375, data_manager.py, 73, INFO, Processing ticker SCHW\n",
+      "2024-10-23 21:14:54,377, data_manager.py, 108, INFO, Getting stock price data for SCHW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:54,377, data_manager.py, 108, INFO, Getting stock price data for SCHW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:54,765, data_manager.py, 82, INFO, Saving data for SCHW by year\n",
+      "2024-10-23 21:14:54,765, data_manager.py, 82, INFO, Saving data for SCHW by year\n",
+      "2024-10-23 21:14:56,053, data_manager.py, 73, INFO, Processing ticker CHTR\n",
+      "2024-10-23 21:14:56,053, data_manager.py, 73, INFO, Processing ticker CHTR\n",
+      "2024-10-23 21:14:56,054, data_manager.py, 108, INFO, Getting stock price data for CHTR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:56,054, data_manager.py, 108, INFO, Getting stock price data for CHTR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:56,265, data_manager.py, 82, INFO, Saving data for CHTR by year\n",
+      "2024-10-23 21:14:56,265, data_manager.py, 82, INFO, Saving data for CHTR by year\n",
+      "2024-10-23 21:14:56,962, data_manager.py, 73, INFO, Processing ticker CVX\n",
+      "2024-10-23 21:14:56,962, data_manager.py, 73, INFO, Processing ticker CVX\n",
+      "2024-10-23 21:14:56,963, data_manager.py, 108, INFO, Getting stock price data for CVX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:56,963, data_manager.py, 108, INFO, Getting stock price data for CVX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:57,332, data_manager.py, 82, INFO, Saving data for CVX by year\n",
+      "2024-10-23 21:14:57,332, data_manager.py, 82, INFO, Saving data for CVX by year\n",
+      "2024-10-23 21:14:58,638, data_manager.py, 73, INFO, Processing ticker CMG\n",
+      "2024-10-23 21:14:58,638, data_manager.py, 73, INFO, Processing ticker CMG\n",
+      "2024-10-23 21:14:58,640, data_manager.py, 108, INFO, Getting stock price data for CMG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:58,640, data_manager.py, 108, INFO, Getting stock price data for CMG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:58,923, data_manager.py, 82, INFO, Saving data for CMG by year\n",
+      "2024-10-23 21:14:58,923, data_manager.py, 82, INFO, Saving data for CMG by year\n",
+      "2024-10-23 21:14:59,771, data_manager.py, 73, INFO, Processing ticker CB\n",
+      "2024-10-23 21:14:59,771, data_manager.py, 73, INFO, Processing ticker CB\n",
+      "2024-10-23 21:14:59,772, data_manager.py, 108, INFO, Getting stock price data for CB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:14:59,772, data_manager.py, 108, INFO, Getting stock price data for CB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:14:59,990, data_manager.py, 82, INFO, Saving data for CB by year\n",
+      "2024-10-23 21:14:59,990, data_manager.py, 82, INFO, Saving data for CB by year\n",
+      "2024-10-23 21:15:01,182, data_manager.py, 73, INFO, Processing ticker CHD\n",
+      "2024-10-23 21:15:01,182, data_manager.py, 73, INFO, Processing ticker CHD\n",
+      "2024-10-23 21:15:01,184, data_manager.py, 108, INFO, Getting stock price data for CHD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:01,184, data_manager.py, 108, INFO, Getting stock price data for CHD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:01,468, data_manager.py, 82, INFO, Saving data for CHD by year\n",
+      "2024-10-23 21:15:01,468, data_manager.py, 82, INFO, Saving data for CHD by year\n",
+      "2024-10-23 21:15:02,605, data_manager.py, 73, INFO, Processing ticker CI\n",
+      "2024-10-23 21:15:02,605, data_manager.py, 73, INFO, Processing ticker CI\n",
+      "2024-10-23 21:15:02,606, data_manager.py, 108, INFO, Getting stock price data for CI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:02,606, data_manager.py, 108, INFO, Getting stock price data for CI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:02,975, data_manager.py, 82, INFO, Saving data for CI by year\n",
+      "2024-10-23 21:15:02,975, data_manager.py, 82, INFO, Saving data for CI by year\n",
+      "2024-10-23 21:15:04,211, data_manager.py, 73, INFO, Processing ticker CINF\n",
+      "2024-10-23 21:15:04,211, data_manager.py, 73, INFO, Processing ticker CINF\n",
+      "2024-10-23 21:15:04,213, data_manager.py, 108, INFO, Getting stock price data for CINF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:04,213, data_manager.py, 108, INFO, Getting stock price data for CINF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:04,521, data_manager.py, 82, INFO, Saving data for CINF by year\n",
+      "2024-10-23 21:15:04,521, data_manager.py, 82, INFO, Saving data for CINF by year\n",
+      "2024-10-23 21:15:05,815, data_manager.py, 73, INFO, Processing ticker CTAS\n",
+      "2024-10-23 21:15:05,815, data_manager.py, 73, INFO, Processing ticker CTAS\n",
+      "2024-10-23 21:15:05,817, data_manager.py, 108, INFO, Getting stock price data for CTAS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:05,817, data_manager.py, 108, INFO, Getting stock price data for CTAS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:06,159, data_manager.py, 82, INFO, Saving data for CTAS by year\n",
+      "2024-10-23 21:15:06,159, data_manager.py, 82, INFO, Saving data for CTAS by year\n",
+      "2024-10-23 21:15:07,491, data_manager.py, 73, INFO, Processing ticker CSCO\n",
+      "2024-10-23 21:15:07,491, data_manager.py, 73, INFO, Processing ticker CSCO\n",
+      "2024-10-23 21:15:07,492, data_manager.py, 108, INFO, Getting stock price data for CSCO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:07,492, data_manager.py, 108, INFO, Getting stock price data for CSCO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:07,742, data_manager.py, 82, INFO, Saving data for CSCO by year\n",
+      "2024-10-23 21:15:07,742, data_manager.py, 82, INFO, Saving data for CSCO by year\n",
+      "2024-10-23 21:15:08,936, data_manager.py, 73, INFO, Processing ticker C\n",
+      "2024-10-23 21:15:08,936, data_manager.py, 73, INFO, Processing ticker C\n",
+      "2024-10-23 21:15:08,938, data_manager.py, 108, INFO, Getting stock price data for C from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:08,938, data_manager.py, 108, INFO, Getting stock price data for C from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:09,194, data_manager.py, 82, INFO, Saving data for C by year\n",
+      "2024-10-23 21:15:09,194, data_manager.py, 82, INFO, Saving data for C by year\n",
+      "2024-10-23 21:15:10,479, data_manager.py, 73, INFO, Processing ticker CFG\n",
+      "2024-10-23 21:15:10,479, data_manager.py, 73, INFO, Processing ticker CFG\n",
+      "2024-10-23 21:15:10,481, data_manager.py, 108, INFO, Getting stock price data for CFG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:10,481, data_manager.py, 108, INFO, Getting stock price data for CFG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:10,636, data_manager.py, 82, INFO, Saving data for CFG by year\n",
+      "2024-10-23 21:15:10,636, data_manager.py, 82, INFO, Saving data for CFG by year\n",
+      "2024-10-23 21:15:11,186, data_manager.py, 73, INFO, Processing ticker CLX\n",
+      "2024-10-23 21:15:11,186, data_manager.py, 73, INFO, Processing ticker CLX\n",
+      "2024-10-23 21:15:11,187, data_manager.py, 108, INFO, Getting stock price data for CLX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:11,187, data_manager.py, 108, INFO, Getting stock price data for CLX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:11,443, data_manager.py, 82, INFO, Saving data for CLX by year\n",
+      "2024-10-23 21:15:11,443, data_manager.py, 82, INFO, Saving data for CLX by year\n",
+      "2024-10-23 21:15:12,592, data_manager.py, 73, INFO, Processing ticker CME\n",
+      "2024-10-23 21:15:12,592, data_manager.py, 73, INFO, Processing ticker CME\n",
+      "2024-10-23 21:15:12,594, data_manager.py, 108, INFO, Getting stock price data for CME from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:12,594, data_manager.py, 108, INFO, Getting stock price data for CME from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:12,848, data_manager.py, 82, INFO, Saving data for CME by year\n",
+      "2024-10-23 21:15:12,848, data_manager.py, 82, INFO, Saving data for CME by year\n",
+      "2024-10-23 21:15:13,982, data_manager.py, 73, INFO, Processing ticker CMS\n",
+      "2024-10-23 21:15:13,982, data_manager.py, 73, INFO, Processing ticker CMS\n",
+      "2024-10-23 21:15:13,983, data_manager.py, 108, INFO, Getting stock price data for CMS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:13,983, data_manager.py, 108, INFO, Getting stock price data for CMS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:14,304, data_manager.py, 82, INFO, Saving data for CMS by year\n",
+      "2024-10-23 21:15:14,304, data_manager.py, 82, INFO, Saving data for CMS by year\n",
+      "2024-10-23 21:15:15,488, data_manager.py, 73, INFO, Processing ticker KO\n",
+      "2024-10-23 21:15:15,488, data_manager.py, 73, INFO, Processing ticker KO\n",
+      "2024-10-23 21:15:15,490, data_manager.py, 108, INFO, Getting stock price data for KO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:15,490, data_manager.py, 108, INFO, Getting stock price data for KO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:15,856, data_manager.py, 82, INFO, Saving data for KO by year\n",
+      "2024-10-23 21:15:15,856, data_manager.py, 82, INFO, Saving data for KO by year\n",
+      "2024-10-23 21:15:17,067, data_manager.py, 73, INFO, Processing ticker CTSH\n",
+      "2024-10-23 21:15:17,067, data_manager.py, 73, INFO, Processing ticker CTSH\n",
+      "2024-10-23 21:15:17,069, data_manager.py, 108, INFO, Getting stock price data for CTSH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:17,069, data_manager.py, 108, INFO, Getting stock price data for CTSH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:17,282, data_manager.py, 82, INFO, Saving data for CTSH by year\n",
+      "2024-10-23 21:15:17,282, data_manager.py, 82, INFO, Saving data for CTSH by year\n",
+      "2024-10-23 21:15:18,458, data_manager.py, 73, INFO, Processing ticker CL\n",
+      "2024-10-23 21:15:18,458, data_manager.py, 73, INFO, Processing ticker CL\n",
+      "2024-10-23 21:15:18,461, data_manager.py, 108, INFO, Getting stock price data for CL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:18,461, data_manager.py, 108, INFO, Getting stock price data for CL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:18,744, data_manager.py, 82, INFO, Saving data for CL by year\n",
+      "2024-10-23 21:15:18,744, data_manager.py, 82, INFO, Saving data for CL by year\n",
+      "2024-10-23 21:15:20,054, data_manager.py, 73, INFO, Processing ticker CMCSA\n",
+      "2024-10-23 21:15:20,054, data_manager.py, 73, INFO, Processing ticker CMCSA\n",
+      "2024-10-23 21:15:20,056, data_manager.py, 108, INFO, Getting stock price data for CMCSA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:20,056, data_manager.py, 108, INFO, Getting stock price data for CMCSA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:20,311, data_manager.py, 82, INFO, Saving data for CMCSA by year\n",
+      "2024-10-23 21:15:20,311, data_manager.py, 82, INFO, Saving data for CMCSA by year\n",
+      "2024-10-23 21:15:21,613, data_manager.py, 73, INFO, Processing ticker CMA\n",
+      "2024-10-23 21:15:21,613, data_manager.py, 73, INFO, Processing ticker CMA\n",
+      "2024-10-23 21:15:21,614, data_manager.py, 108, INFO, Getting stock price data for CMA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:21,614, data_manager.py, 108, INFO, Getting stock price data for CMA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:21,830, data_manager.py, 82, INFO, Saving data for CMA by year\n",
+      "2024-10-23 21:15:21,830, data_manager.py, 82, INFO, Saving data for CMA by year\n",
+      "2024-10-23 21:15:22,998, data_manager.py, 73, INFO, Processing ticker CAG\n",
+      "2024-10-23 21:15:22,998, data_manager.py, 73, INFO, Processing ticker CAG\n",
+      "2024-10-23 21:15:23,000, data_manager.py, 108, INFO, Getting stock price data for CAG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:23,000, data_manager.py, 108, INFO, Getting stock price data for CAG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:23,299, data_manager.py, 82, INFO, Saving data for CAG by year\n",
+      "2024-10-23 21:15:23,299, data_manager.py, 82, INFO, Saving data for CAG by year\n",
+      "2024-10-23 21:15:24,478, data_manager.py, 73, INFO, Processing ticker COP\n",
+      "2024-10-23 21:15:24,478, data_manager.py, 73, INFO, Processing ticker COP\n",
+      "2024-10-23 21:15:24,480, data_manager.py, 108, INFO, Getting stock price data for COP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:24,480, data_manager.py, 108, INFO, Getting stock price data for COP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:24,806, data_manager.py, 82, INFO, Saving data for COP by year\n",
+      "2024-10-23 21:15:24,806, data_manager.py, 82, INFO, Saving data for COP by year\n",
+      "2024-10-23 21:15:26,236, data_manager.py, 73, INFO, Processing ticker ED\n",
+      "2024-10-23 21:15:26,236, data_manager.py, 73, INFO, Processing ticker ED\n",
+      "2024-10-23 21:15:26,238, data_manager.py, 108, INFO, Getting stock price data for ED from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:26,238, data_manager.py, 108, INFO, Getting stock price data for ED from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:26,705, data_manager.py, 82, INFO, Saving data for ED by year\n",
+      "2024-10-23 21:15:26,705, data_manager.py, 82, INFO, Saving data for ED by year\n",
+      "2024-10-23 21:15:27,951, data_manager.py, 73, INFO, Processing ticker STZ\n",
+      "2024-10-23 21:15:27,951, data_manager.py, 73, INFO, Processing ticker STZ\n",
+      "2024-10-23 21:15:27,953, data_manager.py, 108, INFO, Getting stock price data for STZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:27,953, data_manager.py, 108, INFO, Getting stock price data for STZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:28,186, data_manager.py, 82, INFO, Saving data for STZ by year\n",
+      "2024-10-23 21:15:28,186, data_manager.py, 82, INFO, Saving data for STZ by year\n",
+      "2024-10-23 21:15:29,551, data_manager.py, 73, INFO, Processing ticker CEG\n",
+      "2024-10-23 21:15:29,551, data_manager.py, 73, INFO, Processing ticker CEG\n",
+      "2024-10-23 21:15:29,553, data_manager.py, 108, INFO, Getting stock price data for CEG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:29,553, data_manager.py, 108, INFO, Getting stock price data for CEG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:29,689, data_manager.py, 82, INFO, Saving data for CEG by year\n",
+      "2024-10-23 21:15:29,689, data_manager.py, 82, INFO, Saving data for CEG by year\n",
+      "2024-10-23 21:15:29,841, data_manager.py, 73, INFO, Processing ticker COO\n",
+      "2024-10-23 21:15:29,841, data_manager.py, 73, INFO, Processing ticker COO\n",
+      "2024-10-23 21:15:29,843, data_manager.py, 108, INFO, Getting stock price data for COO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:29,843, data_manager.py, 108, INFO, Getting stock price data for COO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:30,127, data_manager.py, 82, INFO, Saving data for COO by year\n",
+      "2024-10-23 21:15:30,127, data_manager.py, 82, INFO, Saving data for COO by year\n",
+      "2024-10-23 21:15:31,463, data_manager.py, 73, INFO, Processing ticker CPRT\n",
+      "2024-10-23 21:15:31,463, data_manager.py, 73, INFO, Processing ticker CPRT\n",
+      "2024-10-23 21:15:31,464, data_manager.py, 108, INFO, Getting stock price data for CPRT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:31,464, data_manager.py, 108, INFO, Getting stock price data for CPRT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:31,710, data_manager.py, 82, INFO, Saving data for CPRT by year\n",
+      "2024-10-23 21:15:31,710, data_manager.py, 82, INFO, Saving data for CPRT by year\n",
+      "2024-10-23 21:15:32,900, data_manager.py, 73, INFO, Processing ticker GLW\n",
+      "2024-10-23 21:15:32,900, data_manager.py, 73, INFO, Processing ticker GLW\n",
+      "2024-10-23 21:15:32,902, data_manager.py, 108, INFO, Getting stock price data for GLW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:32,902, data_manager.py, 108, INFO, Getting stock price data for GLW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:33,227, data_manager.py, 82, INFO, Saving data for GLW by year\n",
+      "2024-10-23 21:15:33,227, data_manager.py, 82, INFO, Saving data for GLW by year\n",
+      "2024-10-23 21:15:34,296, data_manager.py, 73, INFO, Processing ticker CTVA\n",
+      "2024-10-23 21:15:34,296, data_manager.py, 73, INFO, Processing ticker CTVA\n",
+      "2024-10-23 21:15:34,297, data_manager.py, 108, INFO, Getting stock price data for CTVA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:34,297, data_manager.py, 108, INFO, Getting stock price data for CTVA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:34,454, data_manager.py, 82, INFO, Saving data for CTVA by year\n",
+      "2024-10-23 21:15:34,454, data_manager.py, 82, INFO, Saving data for CTVA by year\n",
+      "2024-10-23 21:15:34,688, data_manager.py, 73, INFO, Processing ticker CSGP\n",
+      "2024-10-23 21:15:34,688, data_manager.py, 73, INFO, Processing ticker CSGP\n",
+      "2024-10-23 21:15:34,690, data_manager.py, 108, INFO, Getting stock price data for CSGP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:34,690, data_manager.py, 108, INFO, Getting stock price data for CSGP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:34,923, data_manager.py, 82, INFO, Saving data for CSGP by year\n",
+      "2024-10-23 21:15:34,923, data_manager.py, 82, INFO, Saving data for CSGP by year\n",
+      "2024-10-23 21:15:36,148, data_manager.py, 73, INFO, Processing ticker COST\n",
+      "2024-10-23 21:15:36,148, data_manager.py, 73, INFO, Processing ticker COST\n",
+      "2024-10-23 21:15:36,151, data_manager.py, 108, INFO, Getting stock price data for COST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:36,151, data_manager.py, 108, INFO, Getting stock price data for COST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:36,456, data_manager.py, 82, INFO, Saving data for COST by year\n",
+      "2024-10-23 21:15:36,456, data_manager.py, 82, INFO, Saving data for COST by year\n",
+      "2024-10-23 21:15:37,755, data_manager.py, 73, INFO, Processing ticker CTRA\n",
+      "2024-10-23 21:15:37,755, data_manager.py, 73, INFO, Processing ticker CTRA\n",
+      "2024-10-23 21:15:37,757, data_manager.py, 108, INFO, Getting stock price data for CTRA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:37,757, data_manager.py, 108, INFO, Getting stock price data for CTRA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:38,106, data_manager.py, 82, INFO, Saving data for CTRA by year\n",
+      "2024-10-23 21:15:38,106, data_manager.py, 82, INFO, Saving data for CTRA by year\n",
+      "2024-10-23 21:15:39,337, data_manager.py, 73, INFO, Processing ticker CCI\n",
+      "2024-10-23 21:15:39,337, data_manager.py, 73, INFO, Processing ticker CCI\n",
+      "2024-10-23 21:15:39,339, data_manager.py, 108, INFO, Getting stock price data for CCI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:39,339, data_manager.py, 108, INFO, Getting stock price data for CCI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:39,590, data_manager.py, 82, INFO, Saving data for CCI by year\n",
+      "2024-10-23 21:15:39,590, data_manager.py, 82, INFO, Saving data for CCI by year\n",
+      "2024-10-23 21:15:40,785, data_manager.py, 73, INFO, Processing ticker CSX\n",
+      "2024-10-23 21:15:40,785, data_manager.py, 73, INFO, Processing ticker CSX\n",
+      "2024-10-23 21:15:40,786, data_manager.py, 108, INFO, Getting stock price data for CSX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:40,786, data_manager.py, 108, INFO, Getting stock price data for CSX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:41,111, data_manager.py, 82, INFO, Saving data for CSX by year\n",
+      "2024-10-23 21:15:41,111, data_manager.py, 82, INFO, Saving data for CSX by year\n",
+      "2024-10-23 21:15:42,433, data_manager.py, 73, INFO, Processing ticker CMI\n",
+      "2024-10-23 21:15:42,433, data_manager.py, 73, INFO, Processing ticker CMI\n",
+      "2024-10-23 21:15:42,435, data_manager.py, 108, INFO, Getting stock price data for CMI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:42,435, data_manager.py, 108, INFO, Getting stock price data for CMI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:42,851, data_manager.py, 82, INFO, Saving data for CMI by year\n",
+      "2024-10-23 21:15:42,851, data_manager.py, 82, INFO, Saving data for CMI by year\n",
+      "2024-10-23 21:15:44,063, data_manager.py, 73, INFO, Processing ticker CVS\n",
+      "2024-10-23 21:15:44,063, data_manager.py, 73, INFO, Processing ticker CVS\n",
+      "2024-10-23 21:15:44,064, data_manager.py, 108, INFO, Getting stock price data for CVS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:44,064, data_manager.py, 108, INFO, Getting stock price data for CVS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:44,505, data_manager.py, 82, INFO, Saving data for CVS by year\n",
+      "2024-10-23 21:15:44,505, data_manager.py, 82, INFO, Saving data for CVS by year\n",
+      "2024-10-23 21:15:45,799, data_manager.py, 73, INFO, Processing ticker DHR\n",
+      "2024-10-23 21:15:45,799, data_manager.py, 73, INFO, Processing ticker DHR\n",
+      "2024-10-23 21:15:45,801, data_manager.py, 108, INFO, Getting stock price data for DHR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:45,801, data_manager.py, 108, INFO, Getting stock price data for DHR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:46,202, data_manager.py, 82, INFO, Saving data for DHR by year\n",
+      "2024-10-23 21:15:46,202, data_manager.py, 82, INFO, Saving data for DHR by year\n",
+      "2024-10-23 21:15:47,522, data_manager.py, 73, INFO, Processing ticker DRI\n",
+      "2024-10-23 21:15:47,522, data_manager.py, 73, INFO, Processing ticker DRI\n",
+      "2024-10-23 21:15:47,524, data_manager.py, 108, INFO, Getting stock price data for DRI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:47,524, data_manager.py, 108, INFO, Getting stock price data for DRI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:47,864, data_manager.py, 82, INFO, Saving data for DRI by year\n",
+      "2024-10-23 21:15:47,864, data_manager.py, 82, INFO, Saving data for DRI by year\n",
+      "2024-10-23 21:15:49,109, data_manager.py, 73, INFO, Processing ticker DVA\n",
+      "2024-10-23 21:15:49,109, data_manager.py, 73, INFO, Processing ticker DVA\n",
+      "2024-10-23 21:15:49,111, data_manager.py, 108, INFO, Getting stock price data for DVA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:49,111, data_manager.py, 108, INFO, Getting stock price data for DVA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:49,360, data_manager.py, 82, INFO, Saving data for DVA by year\n",
+      "2024-10-23 21:15:49,360, data_manager.py, 82, INFO, Saving data for DVA by year\n",
+      "2024-10-23 21:15:50,610, data_manager.py, 73, INFO, Processing ticker DAY\n",
+      "2024-10-23 21:15:50,610, data_manager.py, 73, INFO, Processing ticker DAY\n",
+      "2024-10-23 21:15:50,611, data_manager.py, 108, INFO, Getting stock price data for DAY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:50,611, data_manager.py, 108, INFO, Getting stock price data for DAY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:50,748, data_manager.py, 82, INFO, Saving data for DAY by year\n",
+      "2024-10-23 21:15:50,748, data_manager.py, 82, INFO, Saving data for DAY by year\n",
+      "2024-10-23 21:15:51,079, data_manager.py, 73, INFO, Processing ticker DE\n",
+      "2024-10-23 21:15:51,079, data_manager.py, 73, INFO, Processing ticker DE\n",
+      "2024-10-23 21:15:51,081, data_manager.py, 108, INFO, Getting stock price data for DE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:51,081, data_manager.py, 108, INFO, Getting stock price data for DE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:51,466, data_manager.py, 82, INFO, Saving data for DE by year\n",
+      "2024-10-23 21:15:51,466, data_manager.py, 82, INFO, Saving data for DE by year\n",
+      "2024-10-23 21:15:52,750, data_manager.py, 73, INFO, Processing ticker DAL\n",
+      "2024-10-23 21:15:52,750, data_manager.py, 73, INFO, Processing ticker DAL\n",
+      "2024-10-23 21:15:52,751, data_manager.py, 108, INFO, Getting stock price data for DAL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:52,751, data_manager.py, 108, INFO, Getting stock price data for DAL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:53,054, data_manager.py, 82, INFO, Saving data for DAL by year\n",
+      "2024-10-23 21:15:53,054, data_manager.py, 82, INFO, Saving data for DAL by year\n",
+      "2024-10-23 21:15:53,931, data_manager.py, 73, INFO, Processing ticker XRAY\n",
+      "2024-10-23 21:15:53,931, data_manager.py, 73, INFO, Processing ticker XRAY\n",
+      "2024-10-23 21:15:53,932, data_manager.py, 108, INFO, Getting stock price data for XRAY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:53,932, data_manager.py, 108, INFO, Getting stock price data for XRAY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:54,160, data_manager.py, 82, INFO, Saving data for XRAY by year\n",
+      "2024-10-23 21:15:54,160, data_manager.py, 82, INFO, Saving data for XRAY by year\n",
+      "2024-10-23 21:15:55,428, data_manager.py, 73, INFO, Processing ticker DVN\n",
+      "2024-10-23 21:15:55,428, data_manager.py, 73, INFO, Processing ticker DVN\n",
+      "2024-10-23 21:15:55,429, data_manager.py, 108, INFO, Getting stock price data for DVN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:55,429, data_manager.py, 108, INFO, Getting stock price data for DVN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:55,675, data_manager.py, 82, INFO, Saving data for DVN by year\n",
+      "2024-10-23 21:15:55,675, data_manager.py, 82, INFO, Saving data for DVN by year\n",
+      "2024-10-23 21:15:56,886, data_manager.py, 73, INFO, Processing ticker DXCM\n",
+      "2024-10-23 21:15:56,886, data_manager.py, 73, INFO, Processing ticker DXCM\n",
+      "2024-10-23 21:15:56,888, data_manager.py, 108, INFO, Getting stock price data for DXCM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:56,888, data_manager.py, 108, INFO, Getting stock price data for DXCM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:57,083, data_manager.py, 82, INFO, Saving data for DXCM by year\n",
+      "2024-10-23 21:15:57,083, data_manager.py, 82, INFO, Saving data for DXCM by year\n",
+      "2024-10-23 21:15:58,249, data_manager.py, 73, INFO, Processing ticker FANG\n",
+      "2024-10-23 21:15:58,249, data_manager.py, 73, INFO, Processing ticker FANG\n",
+      "2024-10-23 21:15:58,250, data_manager.py, 108, INFO, Getting stock price data for FANG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:58,250, data_manager.py, 108, INFO, Getting stock price data for FANG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:58,554, data_manager.py, 82, INFO, Saving data for FANG by year\n",
+      "2024-10-23 21:15:58,554, data_manager.py, 82, INFO, Saving data for FANG by year\n",
+      "2024-10-23 21:15:59,304, data_manager.py, 73, INFO, Processing ticker DLR\n",
+      "2024-10-23 21:15:59,304, data_manager.py, 73, INFO, Processing ticker DLR\n",
+      "2024-10-23 21:15:59,305, data_manager.py, 108, INFO, Getting stock price data for DLR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:15:59,305, data_manager.py, 108, INFO, Getting stock price data for DLR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:15:59,570, data_manager.py, 82, INFO, Saving data for DLR by year\n",
+      "2024-10-23 21:15:59,570, data_manager.py, 82, INFO, Saving data for DLR by year\n",
+      "2024-10-23 21:16:00,646, data_manager.py, 73, INFO, Processing ticker DFS\n",
+      "2024-10-23 21:16:00,646, data_manager.py, 73, INFO, Processing ticker DFS\n",
+      "2024-10-23 21:16:00,647, data_manager.py, 108, INFO, Getting stock price data for DFS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:00,647, data_manager.py, 108, INFO, Getting stock price data for DFS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:00,839, data_manager.py, 82, INFO, Saving data for DFS by year\n",
+      "2024-10-23 21:16:00,839, data_manager.py, 82, INFO, Saving data for DFS by year\n",
+      "2024-10-23 21:16:01,807, data_manager.py, 73, INFO, Processing ticker DG\n",
+      "2024-10-23 21:16:01,807, data_manager.py, 73, INFO, Processing ticker DG\n",
+      "2024-10-23 21:16:01,810, data_manager.py, 108, INFO, Getting stock price data for DG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:01,810, data_manager.py, 108, INFO, Getting stock price data for DG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:01,972, data_manager.py, 82, INFO, Saving data for DG by year\n",
+      "2024-10-23 21:16:01,972, data_manager.py, 82, INFO, Saving data for DG by year\n",
+      "2024-10-23 21:16:02,762, data_manager.py, 73, INFO, Processing ticker DLTR\n",
+      "2024-10-23 21:16:02,762, data_manager.py, 73, INFO, Processing ticker DLTR\n",
+      "2024-10-23 21:16:02,764, data_manager.py, 108, INFO, Getting stock price data for DLTR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:02,764, data_manager.py, 108, INFO, Getting stock price data for DLTR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:02,932, data_manager.py, 82, INFO, Saving data for DLTR by year\n",
+      "2024-10-23 21:16:02,932, data_manager.py, 82, INFO, Saving data for DLTR by year\n",
+      "2024-10-23 21:16:04,237, data_manager.py, 73, INFO, Processing ticker D\n",
+      "2024-10-23 21:16:04,237, data_manager.py, 73, INFO, Processing ticker D\n",
+      "2024-10-23 21:16:04,239, data_manager.py, 108, INFO, Getting stock price data for D from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:04,239, data_manager.py, 108, INFO, Getting stock price data for D from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:04,530, data_manager.py, 82, INFO, Saving data for D by year\n",
+      "2024-10-23 21:16:04,530, data_manager.py, 82, INFO, Saving data for D by year\n",
+      "2024-10-23 21:16:06,012, data_manager.py, 73, INFO, Processing ticker DPZ\n",
+      "2024-10-23 21:16:06,012, data_manager.py, 73, INFO, Processing ticker DPZ\n",
+      "2024-10-23 21:16:06,014, data_manager.py, 108, INFO, Getting stock price data for DPZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:06,014, data_manager.py, 108, INFO, Getting stock price data for DPZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:06,291, data_manager.py, 82, INFO, Saving data for DPZ by year\n",
+      "2024-10-23 21:16:06,291, data_manager.py, 82, INFO, Saving data for DPZ by year\n",
+      "2024-10-23 21:16:07,455, data_manager.py, 73, INFO, Processing ticker DOV\n",
+      "2024-10-23 21:16:07,455, data_manager.py, 73, INFO, Processing ticker DOV\n",
+      "2024-10-23 21:16:07,458, data_manager.py, 108, INFO, Getting stock price data for DOV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:07,458, data_manager.py, 108, INFO, Getting stock price data for DOV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:07,862, data_manager.py, 82, INFO, Saving data for DOV by year\n",
+      "2024-10-23 21:16:07,862, data_manager.py, 82, INFO, Saving data for DOV by year\n",
+      "2024-10-23 21:16:09,278, data_manager.py, 73, INFO, Processing ticker DOW\n",
+      "2024-10-23 21:16:09,278, data_manager.py, 73, INFO, Processing ticker DOW\n",
+      "2024-10-23 21:16:09,280, data_manager.py, 108, INFO, Getting stock price data for DOW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:09,280, data_manager.py, 108, INFO, Getting stock price data for DOW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:09,418, data_manager.py, 82, INFO, Saving data for DOW by year\n",
+      "2024-10-23 21:16:09,418, data_manager.py, 82, INFO, Saving data for DOW by year\n",
+      "2024-10-23 21:16:09,769, data_manager.py, 73, INFO, Processing ticker DHI\n",
+      "2024-10-23 21:16:09,769, data_manager.py, 73, INFO, Processing ticker DHI\n",
+      "2024-10-23 21:16:09,770, data_manager.py, 108, INFO, Getting stock price data for DHI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:09,770, data_manager.py, 108, INFO, Getting stock price data for DHI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:10,003, data_manager.py, 82, INFO, Saving data for DHI by year\n",
+      "2024-10-23 21:16:10,003, data_manager.py, 82, INFO, Saving data for DHI by year\n",
+      "2024-10-23 21:16:11,534, data_manager.py, 73, INFO, Processing ticker DTE\n",
+      "2024-10-23 21:16:11,534, data_manager.py, 73, INFO, Processing ticker DTE\n",
+      "2024-10-23 21:16:11,536, data_manager.py, 108, INFO, Getting stock price data for DTE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:11,536, data_manager.py, 108, INFO, Getting stock price data for DTE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:12,152, data_manager.py, 82, INFO, Saving data for DTE by year\n",
+      "2024-10-23 21:16:12,152, data_manager.py, 82, INFO, Saving data for DTE by year\n",
+      "2024-10-23 21:16:13,465, data_manager.py, 73, INFO, Processing ticker DUK\n",
+      "2024-10-23 21:16:13,465, data_manager.py, 73, INFO, Processing ticker DUK\n",
+      "2024-10-23 21:16:13,467, data_manager.py, 108, INFO, Getting stock price data for DUK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:13,467, data_manager.py, 108, INFO, Getting stock price data for DUK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:13,812, data_manager.py, 82, INFO, Saving data for DUK by year\n",
+      "2024-10-23 21:16:13,812, data_manager.py, 82, INFO, Saving data for DUK by year\n",
+      "2024-10-23 21:16:15,206, data_manager.py, 73, INFO, Processing ticker DD\n",
+      "2024-10-23 21:16:15,206, data_manager.py, 73, INFO, Processing ticker DD\n",
+      "2024-10-23 21:16:15,208, data_manager.py, 108, INFO, Getting stock price data for DD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:15,208, data_manager.py, 108, INFO, Getting stock price data for DD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:15,576, data_manager.py, 82, INFO, Saving data for DD by year\n",
+      "2024-10-23 21:16:15,576, data_manager.py, 82, INFO, Saving data for DD by year\n",
+      "2024-10-23 21:16:17,060, data_manager.py, 73, INFO, Processing ticker EMN\n",
+      "2024-10-23 21:16:17,060, data_manager.py, 73, INFO, Processing ticker EMN\n",
+      "2024-10-23 21:16:17,063, data_manager.py, 108, INFO, Getting stock price data for EMN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:17,063, data_manager.py, 108, INFO, Getting stock price data for EMN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:17,351, data_manager.py, 82, INFO, Saving data for EMN by year\n",
+      "2024-10-23 21:16:17,351, data_manager.py, 82, INFO, Saving data for EMN by year\n",
+      "2024-10-23 21:16:18,591, data_manager.py, 73, INFO, Processing ticker ETN\n",
+      "2024-10-23 21:16:18,591, data_manager.py, 73, INFO, Processing ticker ETN\n",
+      "2024-10-23 21:16:18,593, data_manager.py, 108, INFO, Getting stock price data for ETN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:18,593, data_manager.py, 108, INFO, Getting stock price data for ETN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:19,003, data_manager.py, 82, INFO, Saving data for ETN by year\n",
+      "2024-10-23 21:16:19,003, data_manager.py, 82, INFO, Saving data for ETN by year\n",
+      "2024-10-23 21:16:20,469, data_manager.py, 73, INFO, Processing ticker EBAY\n",
+      "2024-10-23 21:16:20,469, data_manager.py, 73, INFO, Processing ticker EBAY\n",
+      "2024-10-23 21:16:20,471, data_manager.py, 108, INFO, Getting stock price data for EBAY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:20,471, data_manager.py, 108, INFO, Getting stock price data for EBAY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:20,883, data_manager.py, 82, INFO, Saving data for EBAY by year\n",
+      "2024-10-23 21:16:20,883, data_manager.py, 82, INFO, Saving data for EBAY by year\n",
+      "2024-10-23 21:16:22,450, data_manager.py, 73, INFO, Processing ticker ECL\n",
+      "2024-10-23 21:16:22,450, data_manager.py, 73, INFO, Processing ticker ECL\n",
+      "2024-10-23 21:16:22,453, data_manager.py, 108, INFO, Getting stock price data for ECL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:22,453, data_manager.py, 108, INFO, Getting stock price data for ECL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:22,903, data_manager.py, 82, INFO, Saving data for ECL by year\n",
+      "2024-10-23 21:16:22,903, data_manager.py, 82, INFO, Saving data for ECL by year\n",
+      "2024-10-23 21:16:24,332, data_manager.py, 73, INFO, Processing ticker EIX\n",
+      "2024-10-23 21:16:24,332, data_manager.py, 73, INFO, Processing ticker EIX\n",
+      "2024-10-23 21:16:24,336, data_manager.py, 108, INFO, Getting stock price data for EIX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:24,336, data_manager.py, 108, INFO, Getting stock price data for EIX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:24,653, data_manager.py, 82, INFO, Saving data for EIX by year\n",
+      "2024-10-23 21:16:24,653, data_manager.py, 82, INFO, Saving data for EIX by year\n",
+      "2024-10-23 21:16:26,138, data_manager.py, 73, INFO, Processing ticker EW\n",
+      "2024-10-23 21:16:26,138, data_manager.py, 73, INFO, Processing ticker EW\n",
+      "2024-10-23 21:16:26,140, data_manager.py, 108, INFO, Getting stock price data for EW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:26,140, data_manager.py, 108, INFO, Getting stock price data for EW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:26,507, data_manager.py, 82, INFO, Saving data for EW by year\n",
+      "2024-10-23 21:16:26,507, data_manager.py, 82, INFO, Saving data for EW by year\n",
+      "2024-10-23 21:16:27,976, data_manager.py, 73, INFO, Processing ticker EA\n",
+      "2024-10-23 21:16:27,976, data_manager.py, 73, INFO, Processing ticker EA\n",
+      "2024-10-23 21:16:27,978, data_manager.py, 108, INFO, Getting stock price data for EA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:27,978, data_manager.py, 108, INFO, Getting stock price data for EA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:28,343, data_manager.py, 82, INFO, Saving data for EA by year\n",
+      "2024-10-23 21:16:28,343, data_manager.py, 82, INFO, Saving data for EA by year\n",
+      "2024-10-23 21:16:30,013, data_manager.py, 73, INFO, Processing ticker ELV\n",
+      "2024-10-23 21:16:30,013, data_manager.py, 73, INFO, Processing ticker ELV\n",
+      "2024-10-23 21:16:30,016, data_manager.py, 108, INFO, Getting stock price data for ELV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:30,016, data_manager.py, 108, INFO, Getting stock price data for ELV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:30,356, data_manager.py, 82, INFO, Saving data for ELV by year\n",
+      "2024-10-23 21:16:30,356, data_manager.py, 82, INFO, Saving data for ELV by year\n",
+      "2024-10-23 21:16:31,706, data_manager.py, 73, INFO, Processing ticker LLY\n",
+      "2024-10-23 21:16:31,706, data_manager.py, 73, INFO, Processing ticker LLY\n",
+      "2024-10-23 21:16:31,708, data_manager.py, 108, INFO, Getting stock price data for LLY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:31,708, data_manager.py, 108, INFO, Getting stock price data for LLY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:32,134, data_manager.py, 82, INFO, Saving data for LLY by year\n",
+      "2024-10-23 21:16:32,134, data_manager.py, 82, INFO, Saving data for LLY by year\n",
+      "2024-10-23 21:16:33,574, data_manager.py, 73, INFO, Processing ticker EMR\n",
+      "2024-10-23 21:16:33,574, data_manager.py, 73, INFO, Processing ticker EMR\n",
+      "2024-10-23 21:16:33,577, data_manager.py, 108, INFO, Getting stock price data for EMR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:33,577, data_manager.py, 108, INFO, Getting stock price data for EMR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:33,921, data_manager.py, 82, INFO, Saving data for EMR by year\n",
+      "2024-10-23 21:16:33,921, data_manager.py, 82, INFO, Saving data for EMR by year\n",
+      "2024-10-23 21:16:35,484, data_manager.py, 73, INFO, Processing ticker ENPH\n",
+      "2024-10-23 21:16:35,484, data_manager.py, 73, INFO, Processing ticker ENPH\n",
+      "2024-10-23 21:16:35,488, data_manager.py, 108, INFO, Getting stock price data for ENPH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:35,488, data_manager.py, 108, INFO, Getting stock price data for ENPH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:35,606, data_manager.py, 82, INFO, Saving data for ENPH by year\n",
+      "2024-10-23 21:16:35,606, data_manager.py, 82, INFO, Saving data for ENPH by year\n",
+      "2024-10-23 21:16:36,348, data_manager.py, 73, INFO, Processing ticker ETR\n",
+      "2024-10-23 21:16:36,348, data_manager.py, 73, INFO, Processing ticker ETR\n",
+      "2024-10-23 21:16:36,351, data_manager.py, 108, INFO, Getting stock price data for ETR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:36,351, data_manager.py, 108, INFO, Getting stock price data for ETR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:36,600, data_manager.py, 82, INFO, Saving data for ETR by year\n",
+      "2024-10-23 21:16:36,600, data_manager.py, 82, INFO, Saving data for ETR by year\n",
+      "2024-10-23 21:16:38,034, data_manager.py, 73, INFO, Processing ticker EOG\n",
+      "2024-10-23 21:16:38,034, data_manager.py, 73, INFO, Processing ticker EOG\n",
+      "2024-10-23 21:16:38,036, data_manager.py, 108, INFO, Getting stock price data for EOG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:38,036, data_manager.py, 108, INFO, Getting stock price data for EOG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:38,339, data_manager.py, 82, INFO, Saving data for EOG by year\n",
+      "2024-10-23 21:16:38,339, data_manager.py, 82, INFO, Saving data for EOG by year\n",
+      "2024-10-23 21:16:39,672, data_manager.py, 73, INFO, Processing ticker EPAM\n",
+      "2024-10-23 21:16:39,672, data_manager.py, 73, INFO, Processing ticker EPAM\n",
+      "2024-10-23 21:16:39,674, data_manager.py, 108, INFO, Getting stock price data for EPAM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:39,674, data_manager.py, 108, INFO, Getting stock price data for EPAM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:39,806, data_manager.py, 82, INFO, Saving data for EPAM by year\n",
+      "2024-10-23 21:16:39,806, data_manager.py, 82, INFO, Saving data for EPAM by year\n",
+      "2024-10-23 21:16:40,461, data_manager.py, 73, INFO, Processing ticker EQT\n",
+      "2024-10-23 21:16:40,461, data_manager.py, 73, INFO, Processing ticker EQT\n",
+      "2024-10-23 21:16:40,462, data_manager.py, 108, INFO, Getting stock price data for EQT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:40,462, data_manager.py, 108, INFO, Getting stock price data for EQT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:40,851, data_manager.py, 82, INFO, Saving data for EQT by year\n",
+      "2024-10-23 21:16:40,851, data_manager.py, 82, INFO, Saving data for EQT by year\n",
+      "2024-10-23 21:16:41,865, data_manager.py, 73, INFO, Processing ticker EFX\n",
+      "2024-10-23 21:16:41,865, data_manager.py, 73, INFO, Processing ticker EFX\n",
+      "2024-10-23 21:16:41,866, data_manager.py, 108, INFO, Getting stock price data for EFX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:41,866, data_manager.py, 108, INFO, Getting stock price data for EFX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:42,203, data_manager.py, 82, INFO, Saving data for EFX by year\n",
+      "2024-10-23 21:16:42,203, data_manager.py, 82, INFO, Saving data for EFX by year\n",
+      "2024-10-23 21:16:43,240, data_manager.py, 73, INFO, Processing ticker EQIX\n",
+      "2024-10-23 21:16:43,240, data_manager.py, 73, INFO, Processing ticker EQIX\n",
+      "2024-10-23 21:16:43,241, data_manager.py, 108, INFO, Getting stock price data for EQIX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:43,241, data_manager.py, 108, INFO, Getting stock price data for EQIX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:43,442, data_manager.py, 82, INFO, Saving data for EQIX by year\n",
+      "2024-10-23 21:16:43,442, data_manager.py, 82, INFO, Saving data for EQIX by year\n",
+      "2024-10-23 21:16:44,423, data_manager.py, 73, INFO, Processing ticker EQR\n",
+      "2024-10-23 21:16:44,423, data_manager.py, 73, INFO, Processing ticker EQR\n",
+      "2024-10-23 21:16:44,425, data_manager.py, 108, INFO, Getting stock price data for EQR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:44,425, data_manager.py, 108, INFO, Getting stock price data for EQR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:44,674, data_manager.py, 82, INFO, Saving data for EQR by year\n",
+      "2024-10-23 21:16:44,674, data_manager.py, 82, INFO, Saving data for EQR by year\n",
+      "2024-10-23 21:16:45,845, data_manager.py, 73, INFO, Processing ticker ESS\n",
+      "2024-10-23 21:16:45,845, data_manager.py, 73, INFO, Processing ticker ESS\n",
+      "2024-10-23 21:16:45,846, data_manager.py, 108, INFO, Getting stock price data for ESS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:45,846, data_manager.py, 108, INFO, Getting stock price data for ESS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:46,057, data_manager.py, 82, INFO, Saving data for ESS by year\n",
+      "2024-10-23 21:16:46,057, data_manager.py, 82, INFO, Saving data for ESS by year\n",
+      "2024-10-23 21:16:46,989, data_manager.py, 73, INFO, Processing ticker EL\n",
+      "2024-10-23 21:16:46,989, data_manager.py, 73, INFO, Processing ticker EL\n",
+      "2024-10-23 21:16:46,991, data_manager.py, 108, INFO, Getting stock price data for EL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:46,991, data_manager.py, 108, INFO, Getting stock price data for EL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:47,270, data_manager.py, 82, INFO, Saving data for EL by year\n",
+      "2024-10-23 21:16:47,270, data_manager.py, 82, INFO, Saving data for EL by year\n",
+      "2024-10-23 21:16:48,497, data_manager.py, 73, INFO, Processing ticker ETSY\n",
+      "2024-10-23 21:16:48,497, data_manager.py, 73, INFO, Processing ticker ETSY\n",
+      "2024-10-23 21:16:48,498, data_manager.py, 108, INFO, Getting stock price data for ETSY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:48,498, data_manager.py, 108, INFO, Getting stock price data for ETSY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:48,626, data_manager.py, 82, INFO, Saving data for ETSY by year\n",
+      "2024-10-23 21:16:48,626, data_manager.py, 82, INFO, Saving data for ETSY by year\n",
+      "2024-10-23 21:16:49,005, data_manager.py, 73, INFO, Processing ticker EG\n",
+      "2024-10-23 21:16:49,005, data_manager.py, 73, INFO, Processing ticker EG\n",
+      "2024-10-23 21:16:49,006, data_manager.py, 108, INFO, Getting stock price data for EG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:49,006, data_manager.py, 108, INFO, Getting stock price data for EG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:49,237, data_manager.py, 82, INFO, Saving data for EG by year\n",
+      "2024-10-23 21:16:49,237, data_manager.py, 82, INFO, Saving data for EG by year\n",
+      "2024-10-23 21:16:50,460, data_manager.py, 73, INFO, Processing ticker EVRG\n",
+      "2024-10-23 21:16:50,460, data_manager.py, 73, INFO, Processing ticker EVRG\n",
+      "2024-10-23 21:16:50,461, data_manager.py, 108, INFO, Getting stock price data for EVRG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:50,461, data_manager.py, 108, INFO, Getting stock price data for EVRG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:50,673, data_manager.py, 82, INFO, Saving data for EVRG by year\n",
+      "2024-10-23 21:16:50,673, data_manager.py, 82, INFO, Saving data for EVRG by year\n",
+      "2024-10-23 21:16:51,645, data_manager.py, 73, INFO, Processing ticker ES\n",
+      "2024-10-23 21:16:51,645, data_manager.py, 73, INFO, Processing ticker ES\n",
+      "2024-10-23 21:16:51,646, data_manager.py, 108, INFO, Getting stock price data for ES from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:51,646, data_manager.py, 108, INFO, Getting stock price data for ES from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:51,861, data_manager.py, 82, INFO, Saving data for ES by year\n",
+      "2024-10-23 21:16:51,861, data_manager.py, 82, INFO, Saving data for ES by year\n",
+      "2024-10-23 21:16:52,765, data_manager.py, 73, INFO, Processing ticker EXC\n",
+      "2024-10-23 21:16:52,765, data_manager.py, 73, INFO, Processing ticker EXC\n",
+      "2024-10-23 21:16:52,766, data_manager.py, 108, INFO, Getting stock price data for EXC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:52,766, data_manager.py, 108, INFO, Getting stock price data for EXC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:53,143, data_manager.py, 82, INFO, Saving data for EXC by year\n",
+      "2024-10-23 21:16:53,143, data_manager.py, 82, INFO, Saving data for EXC by year\n",
+      "2024-10-23 21:16:54,198, data_manager.py, 73, INFO, Processing ticker EXPE\n",
+      "2024-10-23 21:16:54,198, data_manager.py, 73, INFO, Processing ticker EXPE\n",
+      "2024-10-23 21:16:54,199, data_manager.py, 108, INFO, Getting stock price data for EXPE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:54,199, data_manager.py, 108, INFO, Getting stock price data for EXPE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:54,501, data_manager.py, 82, INFO, Saving data for EXPE by year\n",
+      "2024-10-23 21:16:54,501, data_manager.py, 82, INFO, Saving data for EXPE by year\n",
+      "2024-10-23 21:16:55,702, data_manager.py, 73, INFO, Processing ticker EXPD\n",
+      "2024-10-23 21:16:55,702, data_manager.py, 73, INFO, Processing ticker EXPD\n",
+      "2024-10-23 21:16:55,704, data_manager.py, 108, INFO, Getting stock price data for EXPD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:55,704, data_manager.py, 108, INFO, Getting stock price data for EXPD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:56,045, data_manager.py, 82, INFO, Saving data for EXPD by year\n",
+      "2024-10-23 21:16:56,045, data_manager.py, 82, INFO, Saving data for EXPD by year\n",
+      "2024-10-23 21:16:56,966, data_manager.py, 73, INFO, Processing ticker EXR\n",
+      "2024-10-23 21:16:56,966, data_manager.py, 73, INFO, Processing ticker EXR\n",
+      "2024-10-23 21:16:56,967, data_manager.py, 108, INFO, Getting stock price data for EXR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:56,967, data_manager.py, 108, INFO, Getting stock price data for EXR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:57,185, data_manager.py, 82, INFO, Saving data for EXR by year\n",
+      "2024-10-23 21:16:57,185, data_manager.py, 82, INFO, Saving data for EXR by year\n",
+      "2024-10-23 21:16:58,251, data_manager.py, 73, INFO, Processing ticker XOM\n",
+      "2024-10-23 21:16:58,251, data_manager.py, 73, INFO, Processing ticker XOM\n",
+      "2024-10-23 21:16:58,253, data_manager.py, 108, INFO, Getting stock price data for XOM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:58,253, data_manager.py, 108, INFO, Getting stock price data for XOM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:16:58,584, data_manager.py, 82, INFO, Saving data for XOM by year\n",
+      "2024-10-23 21:16:58,584, data_manager.py, 82, INFO, Saving data for XOM by year\n",
+      "2024-10-23 21:16:59,842, data_manager.py, 73, INFO, Processing ticker FFIV\n",
+      "2024-10-23 21:16:59,842, data_manager.py, 73, INFO, Processing ticker FFIV\n",
+      "2024-10-23 21:16:59,843, data_manager.py, 108, INFO, Getting stock price data for FFIV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:16:59,843, data_manager.py, 108, INFO, Getting stock price data for FFIV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:00,034, data_manager.py, 82, INFO, Saving data for FFIV by year\n",
+      "2024-10-23 21:17:00,034, data_manager.py, 82, INFO, Saving data for FFIV by year\n",
+      "2024-10-23 21:17:01,134, data_manager.py, 73, INFO, Processing ticker FDS\n",
+      "2024-10-23 21:17:01,134, data_manager.py, 73, INFO, Processing ticker FDS\n",
+      "2024-10-23 21:17:01,135, data_manager.py, 108, INFO, Getting stock price data for FDS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:01,135, data_manager.py, 108, INFO, Getting stock price data for FDS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:01,466, data_manager.py, 82, INFO, Saving data for FDS by year\n",
+      "2024-10-23 21:17:01,466, data_manager.py, 82, INFO, Saving data for FDS by year\n",
+      "2024-10-23 21:17:02,457, data_manager.py, 73, INFO, Processing ticker FICO\n",
+      "2024-10-23 21:17:02,457, data_manager.py, 73, INFO, Processing ticker FICO\n",
+      "2024-10-23 21:17:02,458, data_manager.py, 108, INFO, Getting stock price data for FICO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:02,458, data_manager.py, 108, INFO, Getting stock price data for FICO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:02,759, data_manager.py, 82, INFO, Saving data for FICO by year\n",
+      "2024-10-23 21:17:02,759, data_manager.py, 82, INFO, Saving data for FICO by year\n",
+      "2024-10-23 21:17:03,678, data_manager.py, 73, INFO, Processing ticker FAST\n",
+      "2024-10-23 21:17:03,678, data_manager.py, 73, INFO, Processing ticker FAST\n",
+      "2024-10-23 21:17:03,680, data_manager.py, 108, INFO, Getting stock price data for FAST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:03,680, data_manager.py, 108, INFO, Getting stock price data for FAST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:03,932, data_manager.py, 82, INFO, Saving data for FAST by year\n",
+      "2024-10-23 21:17:03,932, data_manager.py, 82, INFO, Saving data for FAST by year\n",
+      "2024-10-23 21:17:05,003, data_manager.py, 73, INFO, Processing ticker FRT\n",
+      "2024-10-23 21:17:05,003, data_manager.py, 73, INFO, Processing ticker FRT\n",
+      "2024-10-23 21:17:05,005, data_manager.py, 108, INFO, Getting stock price data for FRT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:05,005, data_manager.py, 108, INFO, Getting stock price data for FRT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:05,233, data_manager.py, 82, INFO, Saving data for FRT by year\n",
+      "2024-10-23 21:17:05,233, data_manager.py, 82, INFO, Saving data for FRT by year\n",
+      "2024-10-23 21:17:06,309, data_manager.py, 73, INFO, Processing ticker FDX\n",
+      "2024-10-23 21:17:06,309, data_manager.py, 73, INFO, Processing ticker FDX\n",
+      "2024-10-23 21:17:06,311, data_manager.py, 108, INFO, Getting stock price data for FDX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:06,311, data_manager.py, 108, INFO, Getting stock price data for FDX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:06,496, data_manager.py, 82, INFO, Saving data for FDX by year\n",
+      "2024-10-23 21:17:06,496, data_manager.py, 82, INFO, Saving data for FDX by year\n",
+      "2024-10-23 21:17:07,611, data_manager.py, 73, INFO, Processing ticker FIS\n",
+      "2024-10-23 21:17:07,611, data_manager.py, 73, INFO, Processing ticker FIS\n",
+      "2024-10-23 21:17:07,612, data_manager.py, 108, INFO, Getting stock price data for FIS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:07,612, data_manager.py, 108, INFO, Getting stock price data for FIS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:07,775, data_manager.py, 82, INFO, Saving data for FIS by year\n",
+      "2024-10-23 21:17:07,775, data_manager.py, 82, INFO, Saving data for FIS by year\n",
+      "2024-10-23 21:17:29,904, data_manager.py, 73, INFO, Processing ticker FITB\n",
+      "2024-10-23 21:17:29,904, data_manager.py, 73, INFO, Processing ticker FITB\n",
+      "2024-10-23 21:17:29,906, data_manager.py, 108, INFO, Getting stock price data for FITB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:29,906, data_manager.py, 108, INFO, Getting stock price data for FITB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:09,224, data_manager.py, 82, INFO, Saving data for FITB by year\n",
+      "2024-10-23 21:17:09,224, data_manager.py, 82, INFO, Saving data for FITB by year\n",
+      "2024-10-23 21:17:10,556, data_manager.py, 73, INFO, Processing ticker FSLR\n",
+      "2024-10-23 21:17:10,556, data_manager.py, 73, INFO, Processing ticker FSLR\n",
+      "2024-10-23 21:17:10,557, data_manager.py, 108, INFO, Getting stock price data for FSLR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:10,557, data_manager.py, 108, INFO, Getting stock price data for FSLR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:10,848, data_manager.py, 82, INFO, Saving data for FSLR by year\n",
+      "2024-10-23 21:17:10,848, data_manager.py, 82, INFO, Saving data for FSLR by year\n",
+      "2024-10-23 21:17:11,733, data_manager.py, 73, INFO, Processing ticker FE\n",
+      "2024-10-23 21:17:11,733, data_manager.py, 73, INFO, Processing ticker FE\n",
+      "2024-10-23 21:17:11,735, data_manager.py, 108, INFO, Getting stock price data for FE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:11,735, data_manager.py, 108, INFO, Getting stock price data for FE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:12,030, data_manager.py, 82, INFO, Saving data for FE by year\n",
+      "2024-10-23 21:17:12,030, data_manager.py, 82, INFO, Saving data for FE by year\n",
+      "2024-10-23 21:17:13,130, data_manager.py, 73, INFO, Processing ticker FI\n",
+      "2024-10-23 21:17:13,130, data_manager.py, 73, INFO, Processing ticker FI\n",
+      "2024-10-23 21:17:13,132, data_manager.py, 108, INFO, Getting stock price data for FI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:13,132, data_manager.py, 108, INFO, Getting stock price data for FI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:13,410, data_manager.py, 82, INFO, Saving data for FI by year\n",
+      "2024-10-23 21:17:13,410, data_manager.py, 82, INFO, Saving data for FI by year\n",
+      "2024-10-23 21:17:14,240, data_manager.py, 73, INFO, Processing ticker FLT\n",
+      "2024-10-23 21:17:14,240, data_manager.py, 73, INFO, Processing ticker FLT\n",
+      "2024-10-23 21:17:14,241, data_manager.py, 108, INFO, Getting stock price data for FLT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:14,241, data_manager.py, 108, INFO, Getting stock price data for FLT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['FLT']: YFTzMissingError('$%ticker%: possibly delisted; No timezone found')\n",
+      "2024-10-23 21:17:15,501, data_manager.py, 82, INFO, Saving data for FLT by year\n",
+      "2024-10-23 21:17:15,501, data_manager.py, 82, INFO, Saving data for FLT by year\n",
+      "2024-10-23 21:17:15,503, data_manager.py, 100, WARNING, No data found for FLT\n",
+      "2024-10-23 21:17:15,503, data_manager.py, 100, WARNING, No data found for FLT\n",
+      "2024-10-23 21:17:15,505, data_manager.py, 73, INFO, Processing ticker FMC\n",
+      "2024-10-23 21:17:15,505, data_manager.py, 73, INFO, Processing ticker FMC\n",
+      "2024-10-23 21:17:15,507, data_manager.py, 108, INFO, Getting stock price data for FMC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:15,507, data_manager.py, 108, INFO, Getting stock price data for FMC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:15,798, data_manager.py, 82, INFO, Saving data for FMC by year\n",
+      "2024-10-23 21:17:15,798, data_manager.py, 82, INFO, Saving data for FMC by year\n",
+      "2024-10-23 21:17:17,034, data_manager.py, 73, INFO, Processing ticker F\n",
+      "2024-10-23 21:17:17,034, data_manager.py, 73, INFO, Processing ticker F\n",
+      "2024-10-23 21:17:17,036, data_manager.py, 108, INFO, Getting stock price data for F from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:17,036, data_manager.py, 108, INFO, Getting stock price data for F from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:17,420, data_manager.py, 82, INFO, Saving data for F by year\n",
+      "2024-10-23 21:17:17,420, data_manager.py, 82, INFO, Saving data for F by year\n",
+      "2024-10-23 21:17:18,387, data_manager.py, 73, INFO, Processing ticker FTNT\n",
+      "2024-10-23 21:17:18,387, data_manager.py, 73, INFO, Processing ticker FTNT\n",
+      "2024-10-23 21:17:18,389, data_manager.py, 108, INFO, Getting stock price data for FTNT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:18,389, data_manager.py, 108, INFO, Getting stock price data for FTNT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:18,612, data_manager.py, 82, INFO, Saving data for FTNT by year\n",
+      "2024-10-23 21:17:18,612, data_manager.py, 82, INFO, Saving data for FTNT by year\n",
+      "2024-10-23 21:17:19,370, data_manager.py, 73, INFO, Processing ticker FTV\n",
+      "2024-10-23 21:17:19,370, data_manager.py, 73, INFO, Processing ticker FTV\n",
+      "2024-10-23 21:17:19,372, data_manager.py, 108, INFO, Getting stock price data for FTV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:19,372, data_manager.py, 108, INFO, Getting stock price data for FTV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:19,622, data_manager.py, 82, INFO, Saving data for FTV by year\n",
+      "2024-10-23 21:17:19,622, data_manager.py, 82, INFO, Saving data for FTV by year\n",
+      "2024-10-23 21:17:20,078, data_manager.py, 73, INFO, Processing ticker FOXA\n",
+      "2024-10-23 21:17:20,078, data_manager.py, 73, INFO, Processing ticker FOXA\n",
+      "2024-10-23 21:17:20,080, data_manager.py, 108, INFO, Getting stock price data for FOXA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:20,080, data_manager.py, 108, INFO, Getting stock price data for FOXA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:20,218, data_manager.py, 82, INFO, Saving data for FOXA by year\n",
+      "2024-10-23 21:17:20,218, data_manager.py, 82, INFO, Saving data for FOXA by year\n",
+      "2024-10-23 21:17:20,467, data_manager.py, 73, INFO, Processing ticker FOX\n",
+      "2024-10-23 21:17:20,467, data_manager.py, 73, INFO, Processing ticker FOX\n",
+      "2024-10-23 21:17:20,468, data_manager.py, 108, INFO, Getting stock price data for FOX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:20,468, data_manager.py, 108, INFO, Getting stock price data for FOX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:20,604, data_manager.py, 82, INFO, Saving data for FOX by year\n",
+      "2024-10-23 21:17:20,604, data_manager.py, 82, INFO, Saving data for FOX by year\n",
+      "2024-10-23 21:17:20,841, data_manager.py, 73, INFO, Processing ticker BEN\n",
+      "2024-10-23 21:17:20,841, data_manager.py, 73, INFO, Processing ticker BEN\n",
+      "2024-10-23 21:17:20,843, data_manager.py, 108, INFO, Getting stock price data for BEN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:20,843, data_manager.py, 108, INFO, Getting stock price data for BEN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:21,177, data_manager.py, 82, INFO, Saving data for BEN by year\n",
+      "2024-10-23 21:17:21,177, data_manager.py, 82, INFO, Saving data for BEN by year\n",
+      "2024-10-23 21:17:22,377, data_manager.py, 73, INFO, Processing ticker FCX\n",
+      "2024-10-23 21:17:22,377, data_manager.py, 73, INFO, Processing ticker FCX\n",
+      "2024-10-23 21:17:22,379, data_manager.py, 108, INFO, Getting stock price data for FCX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:22,379, data_manager.py, 108, INFO, Getting stock price data for FCX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:22,682, data_manager.py, 82, INFO, Saving data for FCX by year\n",
+      "2024-10-23 21:17:22,682, data_manager.py, 82, INFO, Saving data for FCX by year\n",
+      "2024-10-23 21:17:23,674, data_manager.py, 73, INFO, Processing ticker GRMN\n",
+      "2024-10-23 21:17:23,674, data_manager.py, 73, INFO, Processing ticker GRMN\n",
+      "2024-10-23 21:17:23,675, data_manager.py, 108, INFO, Getting stock price data for GRMN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:23,675, data_manager.py, 108, INFO, Getting stock price data for GRMN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:24,020, data_manager.py, 82, INFO, Saving data for GRMN by year\n",
+      "2024-10-23 21:17:24,020, data_manager.py, 82, INFO, Saving data for GRMN by year\n",
+      "2024-10-23 21:17:24,980, data_manager.py, 73, INFO, Processing ticker IT\n",
+      "2024-10-23 21:17:24,980, data_manager.py, 73, INFO, Processing ticker IT\n",
+      "2024-10-23 21:17:24,982, data_manager.py, 108, INFO, Getting stock price data for IT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:24,982, data_manager.py, 108, INFO, Getting stock price data for IT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:25,269, data_manager.py, 82, INFO, Saving data for IT by year\n",
+      "2024-10-23 21:17:25,269, data_manager.py, 82, INFO, Saving data for IT by year\n",
+      "2024-10-23 21:17:26,307, data_manager.py, 73, INFO, Processing ticker GEHC\n",
+      "2024-10-23 21:17:26,307, data_manager.py, 73, INFO, Processing ticker GEHC\n",
+      "2024-10-23 21:17:26,308, data_manager.py, 108, INFO, Getting stock price data for GEHC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:26,308, data_manager.py, 108, INFO, Getting stock price data for GEHC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:26,434, data_manager.py, 82, INFO, Saving data for GEHC by year\n",
+      "2024-10-23 21:17:26,434, data_manager.py, 82, INFO, Saving data for GEHC by year\n",
+      "2024-10-23 21:17:26,614, data_manager.py, 73, INFO, Processing ticker GEN\n",
+      "2024-10-23 21:17:26,614, data_manager.py, 73, INFO, Processing ticker GEN\n",
+      "2024-10-23 21:17:26,615, data_manager.py, 108, INFO, Getting stock price data for GEN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:26,615, data_manager.py, 108, INFO, Getting stock price data for GEN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:27,027, data_manager.py, 82, INFO, Saving data for GEN by year\n",
+      "2024-10-23 21:17:27,027, data_manager.py, 82, INFO, Saving data for GEN by year\n",
+      "2024-10-23 21:17:28,001, data_manager.py, 73, INFO, Processing ticker GNRC\n",
+      "2024-10-23 21:17:28,001, data_manager.py, 73, INFO, Processing ticker GNRC\n",
+      "2024-10-23 21:17:28,002, data_manager.py, 108, INFO, Getting stock price data for GNRC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:28,002, data_manager.py, 108, INFO, Getting stock price data for GNRC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:28,192, data_manager.py, 82, INFO, Saving data for GNRC by year\n",
+      "2024-10-23 21:17:28,192, data_manager.py, 82, INFO, Saving data for GNRC by year\n",
+      "2024-10-23 21:17:49,915, data_manager.py, 73, INFO, Processing ticker GD\n",
+      "2024-10-23 21:17:49,915, data_manager.py, 73, INFO, Processing ticker GD\n",
+      "2024-10-23 21:17:49,917, data_manager.py, 108, INFO, Getting stock price data for GD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:49,917, data_manager.py, 108, INFO, Getting stock price data for GD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:29,227, data_manager.py, 82, INFO, Saving data for GD by year\n",
+      "2024-10-23 21:17:29,227, data_manager.py, 82, INFO, Saving data for GD by year\n",
+      "2024-10-23 21:17:30,339, data_manager.py, 73, INFO, Processing ticker GE\n",
+      "2024-10-23 21:17:30,339, data_manager.py, 73, INFO, Processing ticker GE\n",
+      "2024-10-23 21:17:30,341, data_manager.py, 108, INFO, Getting stock price data for GE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:30,341, data_manager.py, 108, INFO, Getting stock price data for GE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:30,721, data_manager.py, 82, INFO, Saving data for GE by year\n",
+      "2024-10-23 21:17:30,721, data_manager.py, 82, INFO, Saving data for GE by year\n",
+      "2024-10-23 21:17:31,875, data_manager.py, 73, INFO, Processing ticker GIS\n",
+      "2024-10-23 21:17:31,875, data_manager.py, 73, INFO, Processing ticker GIS\n",
+      "2024-10-23 21:17:31,877, data_manager.py, 108, INFO, Getting stock price data for GIS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:31,877, data_manager.py, 108, INFO, Getting stock price data for GIS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:32,193, data_manager.py, 82, INFO, Saving data for GIS by year\n",
+      "2024-10-23 21:17:32,193, data_manager.py, 82, INFO, Saving data for GIS by year\n",
+      "2024-10-23 21:17:33,257, data_manager.py, 73, INFO, Processing ticker GM\n",
+      "2024-10-23 21:17:33,257, data_manager.py, 73, INFO, Processing ticker GM\n",
+      "2024-10-23 21:17:33,258, data_manager.py, 108, INFO, Getting stock price data for GM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:33,258, data_manager.py, 108, INFO, Getting stock price data for GM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:33,598, data_manager.py, 82, INFO, Saving data for GM by year\n",
+      "2024-10-23 21:17:33,598, data_manager.py, 82, INFO, Saving data for GM by year\n",
+      "2024-10-23 21:17:34,203, data_manager.py, 73, INFO, Processing ticker GPC\n",
+      "2024-10-23 21:17:34,203, data_manager.py, 73, INFO, Processing ticker GPC\n",
+      "2024-10-23 21:17:34,205, data_manager.py, 108, INFO, Getting stock price data for GPC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:34,205, data_manager.py, 108, INFO, Getting stock price data for GPC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:34,579, data_manager.py, 82, INFO, Saving data for GPC by year\n",
+      "2024-10-23 21:17:34,579, data_manager.py, 82, INFO, Saving data for GPC by year\n",
+      "2024-10-23 21:17:35,745, data_manager.py, 73, INFO, Processing ticker GILD\n",
+      "2024-10-23 21:17:35,745, data_manager.py, 73, INFO, Processing ticker GILD\n",
+      "2024-10-23 21:17:35,746, data_manager.py, 108, INFO, Getting stock price data for GILD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:35,746, data_manager.py, 108, INFO, Getting stock price data for GILD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:36,096, data_manager.py, 82, INFO, Saving data for GILD by year\n",
+      "2024-10-23 21:17:36,096, data_manager.py, 82, INFO, Saving data for GILD by year\n",
+      "2024-10-23 21:17:37,209, data_manager.py, 73, INFO, Processing ticker GPN\n",
+      "2024-10-23 21:17:37,209, data_manager.py, 73, INFO, Processing ticker GPN\n",
+      "2024-10-23 21:17:37,211, data_manager.py, 108, INFO, Getting stock price data for GPN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:37,211, data_manager.py, 108, INFO, Getting stock price data for GPN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:37,492, data_manager.py, 82, INFO, Saving data for GPN by year\n",
+      "2024-10-23 21:17:37,492, data_manager.py, 82, INFO, Saving data for GPN by year\n",
+      "2024-10-23 21:17:38,594, data_manager.py, 73, INFO, Processing ticker GL\n",
+      "2024-10-23 21:17:38,594, data_manager.py, 73, INFO, Processing ticker GL\n",
+      "2024-10-23 21:17:38,595, data_manager.py, 108, INFO, Getting stock price data for GL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:38,595, data_manager.py, 108, INFO, Getting stock price data for GL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:59,988, data_manager.py, 82, INFO, Saving data for GL by year\n",
+      "2024-10-23 21:17:59,988, data_manager.py, 82, INFO, Saving data for GL by year\n",
+      "2024-10-23 21:17:39,978, data_manager.py, 73, INFO, Processing ticker GS\n",
+      "2024-10-23 21:17:39,978, data_manager.py, 73, INFO, Processing ticker GS\n",
+      "2024-10-23 21:17:39,980, data_manager.py, 108, INFO, Getting stock price data for GS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:39,980, data_manager.py, 108, INFO, Getting stock price data for GS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:40,227, data_manager.py, 82, INFO, Saving data for GS by year\n",
+      "2024-10-23 21:17:40,227, data_manager.py, 82, INFO, Saving data for GS by year\n",
+      "2024-10-23 21:17:41,376, data_manager.py, 73, INFO, Processing ticker HAL\n",
+      "2024-10-23 21:17:41,376, data_manager.py, 73, INFO, Processing ticker HAL\n",
+      "2024-10-23 21:17:41,378, data_manager.py, 108, INFO, Getting stock price data for HAL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:41,378, data_manager.py, 108, INFO, Getting stock price data for HAL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:41,696, data_manager.py, 82, INFO, Saving data for HAL by year\n",
+      "2024-10-23 21:17:41,696, data_manager.py, 82, INFO, Saving data for HAL by year\n",
+      "2024-10-23 21:17:42,852, data_manager.py, 73, INFO, Processing ticker HIG\n",
+      "2024-10-23 21:17:42,852, data_manager.py, 73, INFO, Processing ticker HIG\n",
+      "2024-10-23 21:17:42,854, data_manager.py, 108, INFO, Getting stock price data for HIG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:42,854, data_manager.py, 108, INFO, Getting stock price data for HIG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:43,162, data_manager.py, 82, INFO, Saving data for HIG by year\n",
+      "2024-10-23 21:17:43,162, data_manager.py, 82, INFO, Saving data for HIG by year\n",
+      "2024-10-23 21:17:44,150, data_manager.py, 73, INFO, Processing ticker HAS\n",
+      "2024-10-23 21:17:44,150, data_manager.py, 73, INFO, Processing ticker HAS\n",
+      "2024-10-23 21:17:44,152, data_manager.py, 108, INFO, Getting stock price data for HAS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:44,152, data_manager.py, 108, INFO, Getting stock price data for HAS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:44,418, data_manager.py, 82, INFO, Saving data for HAS by year\n",
+      "2024-10-23 21:17:44,418, data_manager.py, 82, INFO, Saving data for HAS by year\n",
+      "2024-10-23 21:17:45,446, data_manager.py, 73, INFO, Processing ticker HCA\n",
+      "2024-10-23 21:17:45,446, data_manager.py, 73, INFO, Processing ticker HCA\n",
+      "2024-10-23 21:17:45,448, data_manager.py, 108, INFO, Getting stock price data for HCA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:45,448, data_manager.py, 108, INFO, Getting stock price data for HCA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:45,697, data_manager.py, 82, INFO, Saving data for HCA by year\n",
+      "2024-10-23 21:17:45,697, data_manager.py, 82, INFO, Saving data for HCA by year\n",
+      "2024-10-23 21:17:46,361, data_manager.py, 73, INFO, Processing ticker PEAK\n",
+      "2024-10-23 21:17:46,361, data_manager.py, 73, INFO, Processing ticker PEAK\n",
+      "2024-10-23 21:17:46,362, data_manager.py, 108, INFO, Getting stock price data for PEAK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:46,362, data_manager.py, 108, INFO, Getting stock price data for PEAK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['PEAK']: YFTzMissingError('$%ticker%: possibly delisted; No timezone found')\n",
+      "2024-10-23 21:17:47,084, data_manager.py, 82, INFO, Saving data for PEAK by year\n",
+      "2024-10-23 21:17:47,084, data_manager.py, 82, INFO, Saving data for PEAK by year\n",
+      "2024-10-23 21:17:47,086, data_manager.py, 100, WARNING, No data found for PEAK\n",
+      "2024-10-23 21:17:47,086, data_manager.py, 100, WARNING, No data found for PEAK\n",
+      "2024-10-23 21:17:47,088, data_manager.py, 73, INFO, Processing ticker HSIC\n",
+      "2024-10-23 21:17:47,088, data_manager.py, 73, INFO, Processing ticker HSIC\n",
+      "2024-10-23 21:17:47,090, data_manager.py, 108, INFO, Getting stock price data for HSIC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:47,090, data_manager.py, 108, INFO, Getting stock price data for HSIC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:47,367, data_manager.py, 82, INFO, Saving data for HSIC by year\n",
+      "2024-10-23 21:17:47,367, data_manager.py, 82, INFO, Saving data for HSIC by year\n",
+      "2024-10-23 21:17:48,500, data_manager.py, 73, INFO, Processing ticker HSY\n",
+      "2024-10-23 21:17:48,500, data_manager.py, 73, INFO, Processing ticker HSY\n",
+      "2024-10-23 21:17:48,501, data_manager.py, 108, INFO, Getting stock price data for HSY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:48,501, data_manager.py, 108, INFO, Getting stock price data for HSY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:48,779, data_manager.py, 82, INFO, Saving data for HSY by year\n",
+      "2024-10-23 21:17:48,779, data_manager.py, 82, INFO, Saving data for HSY by year\n",
+      "2024-10-23 21:17:50,036, data_manager.py, 73, INFO, Processing ticker HES\n",
+      "2024-10-23 21:17:50,036, data_manager.py, 73, INFO, Processing ticker HES\n",
+      "2024-10-23 21:17:50,039, data_manager.py, 108, INFO, Getting stock price data for HES from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:50,039, data_manager.py, 108, INFO, Getting stock price data for HES from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:50,332, data_manager.py, 82, INFO, Saving data for HES by year\n",
+      "2024-10-23 21:17:50,332, data_manager.py, 82, INFO, Saving data for HES by year\n",
+      "2024-10-23 21:17:51,345, data_manager.py, 73, INFO, Processing ticker HPE\n",
+      "2024-10-23 21:17:51,345, data_manager.py, 73, INFO, Processing ticker HPE\n",
+      "2024-10-23 21:17:51,347, data_manager.py, 108, INFO, Getting stock price data for HPE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:51,347, data_manager.py, 108, INFO, Getting stock price data for HPE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:51,572, data_manager.py, 82, INFO, Saving data for HPE by year\n",
+      "2024-10-23 21:17:51,572, data_manager.py, 82, INFO, Saving data for HPE by year\n",
+      "2024-10-23 21:17:51,992, data_manager.py, 73, INFO, Processing ticker HLT\n",
+      "2024-10-23 21:17:51,992, data_manager.py, 73, INFO, Processing ticker HLT\n",
+      "2024-10-23 21:17:51,995, data_manager.py, 108, INFO, Getting stock price data for HLT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:51,995, data_manager.py, 108, INFO, Getting stock price data for HLT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:52,224, data_manager.py, 82, INFO, Saving data for HLT by year\n",
+      "2024-10-23 21:17:52,224, data_manager.py, 82, INFO, Saving data for HLT by year\n",
+      "2024-10-23 21:17:52,803, data_manager.py, 73, INFO, Processing ticker HOLX\n",
+      "2024-10-23 21:17:52,803, data_manager.py, 73, INFO, Processing ticker HOLX\n",
+      "2024-10-23 21:17:52,805, data_manager.py, 108, INFO, Getting stock price data for HOLX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:52,805, data_manager.py, 108, INFO, Getting stock price data for HOLX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:52,999, data_manager.py, 82, INFO, Saving data for HOLX by year\n",
+      "2024-10-23 21:17:52,999, data_manager.py, 82, INFO, Saving data for HOLX by year\n",
+      "2024-10-23 21:18:14,974, data_manager.py, 73, INFO, Processing ticker HD\n",
+      "2024-10-23 21:18:14,974, data_manager.py, 73, INFO, Processing ticker HD\n",
+      "2024-10-23 21:18:14,975, data_manager.py, 108, INFO, Getting stock price data for HD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:14,975, data_manager.py, 108, INFO, Getting stock price data for HD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:54,233, data_manager.py, 82, INFO, Saving data for HD by year\n",
+      "2024-10-23 21:17:54,233, data_manager.py, 82, INFO, Saving data for HD by year\n",
+      "2024-10-23 21:17:55,495, data_manager.py, 73, INFO, Processing ticker HON\n",
+      "2024-10-23 21:17:55,495, data_manager.py, 73, INFO, Processing ticker HON\n",
+      "2024-10-23 21:17:55,497, data_manager.py, 108, INFO, Getting stock price data for HON from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:55,497, data_manager.py, 108, INFO, Getting stock price data for HON from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:55,780, data_manager.py, 82, INFO, Saving data for HON by year\n",
+      "2024-10-23 21:17:55,780, data_manager.py, 82, INFO, Saving data for HON by year\n",
+      "2024-10-23 21:17:56,864, data_manager.py, 73, INFO, Processing ticker HRL\n",
+      "2024-10-23 21:17:56,864, data_manager.py, 73, INFO, Processing ticker HRL\n",
+      "2024-10-23 21:17:56,866, data_manager.py, 108, INFO, Getting stock price data for HRL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:56,866, data_manager.py, 108, INFO, Getting stock price data for HRL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:57,165, data_manager.py, 82, INFO, Saving data for HRL by year\n",
+      "2024-10-23 21:17:57,165, data_manager.py, 82, INFO, Saving data for HRL by year\n",
+      "2024-10-23 21:17:58,119, data_manager.py, 73, INFO, Processing ticker HST\n",
+      "2024-10-23 21:17:58,119, data_manager.py, 73, INFO, Processing ticker HST\n",
+      "2024-10-23 21:17:58,122, data_manager.py, 108, INFO, Getting stock price data for HST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:58,122, data_manager.py, 108, INFO, Getting stock price data for HST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:58,467, data_manager.py, 82, INFO, Saving data for HST by year\n",
+      "2024-10-23 21:17:58,467, data_manager.py, 82, INFO, Saving data for HST by year\n",
+      "2024-10-23 21:17:59,495, data_manager.py, 73, INFO, Processing ticker HWM\n",
+      "2024-10-23 21:17:59,495, data_manager.py, 73, INFO, Processing ticker HWM\n",
+      "2024-10-23 21:17:59,497, data_manager.py, 108, INFO, Getting stock price data for HWM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:17:59,497, data_manager.py, 108, INFO, Getting stock price data for HWM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:17:59,677, data_manager.py, 82, INFO, Saving data for HWM by year\n",
+      "2024-10-23 21:17:59,677, data_manager.py, 82, INFO, Saving data for HWM by year\n",
+      "2024-10-23 21:18:00,012, data_manager.py, 73, INFO, Processing ticker HPQ\n",
+      "2024-10-23 21:18:00,012, data_manager.py, 73, INFO, Processing ticker HPQ\n",
+      "2024-10-23 21:18:00,014, data_manager.py, 108, INFO, Getting stock price data for HPQ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:00,014, data_manager.py, 108, INFO, Getting stock price data for HPQ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:00,319, data_manager.py, 82, INFO, Saving data for HPQ by year\n",
+      "2024-10-23 21:18:00,319, data_manager.py, 82, INFO, Saving data for HPQ by year\n",
+      "2024-10-23 21:18:01,267, data_manager.py, 73, INFO, Processing ticker HUBB\n",
+      "2024-10-23 21:18:01,267, data_manager.py, 73, INFO, Processing ticker HUBB\n",
+      "2024-10-23 21:18:01,268, data_manager.py, 108, INFO, Getting stock price data for HUBB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:01,268, data_manager.py, 108, INFO, Getting stock price data for HUBB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:01,591, data_manager.py, 82, INFO, Saving data for HUBB by year\n",
+      "2024-10-23 21:18:01,591, data_manager.py, 82, INFO, Saving data for HUBB by year\n",
+      "2024-10-23 21:18:02,584, data_manager.py, 73, INFO, Processing ticker HUM\n",
+      "2024-10-23 21:18:02,584, data_manager.py, 73, INFO, Processing ticker HUM\n",
+      "2024-10-23 21:18:02,586, data_manager.py, 108, INFO, Getting stock price data for HUM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:02,586, data_manager.py, 108, INFO, Getting stock price data for HUM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:02,959, data_manager.py, 82, INFO, Saving data for HUM by year\n",
+      "2024-10-23 21:18:02,959, data_manager.py, 82, INFO, Saving data for HUM by year\n",
+      "2024-10-23 21:18:24,979, data_manager.py, 73, INFO, Processing ticker HBAN\n",
+      "2024-10-23 21:18:24,979, data_manager.py, 73, INFO, Processing ticker HBAN\n",
+      "2024-10-23 21:18:24,981, data_manager.py, 108, INFO, Getting stock price data for HBAN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:24,981, data_manager.py, 108, INFO, Getting stock price data for HBAN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:04,256, data_manager.py, 82, INFO, Saving data for HBAN by year\n",
+      "2024-10-23 21:18:04,256, data_manager.py, 82, INFO, Saving data for HBAN by year\n",
+      "2024-10-23 21:18:05,035, data_manager.py, 73, INFO, Processing ticker HII\n",
+      "2024-10-23 21:18:05,035, data_manager.py, 73, INFO, Processing ticker HII\n",
+      "2024-10-23 21:18:05,037, data_manager.py, 108, INFO, Getting stock price data for HII from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:05,037, data_manager.py, 108, INFO, Getting stock price data for HII from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:05,768, data_manager.py, 82, INFO, Saving data for HII by year\n",
+      "2024-10-23 21:18:05,768, data_manager.py, 82, INFO, Saving data for HII by year\n",
+      "2024-10-23 21:18:06,320, data_manager.py, 73, INFO, Processing ticker IBM\n",
+      "2024-10-23 21:18:06,320, data_manager.py, 73, INFO, Processing ticker IBM\n",
+      "2024-10-23 21:18:06,321, data_manager.py, 108, INFO, Getting stock price data for IBM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:06,321, data_manager.py, 108, INFO, Getting stock price data for IBM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:06,648, data_manager.py, 82, INFO, Saving data for IBM by year\n",
+      "2024-10-23 21:18:06,648, data_manager.py, 82, INFO, Saving data for IBM by year\n",
+      "2024-10-23 21:18:07,655, data_manager.py, 73, INFO, Processing ticker IEX\n",
+      "2024-10-23 21:18:07,655, data_manager.py, 73, INFO, Processing ticker IEX\n",
+      "2024-10-23 21:18:07,656, data_manager.py, 108, INFO, Getting stock price data for IEX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:07,656, data_manager.py, 108, INFO, Getting stock price data for IEX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:07,905, data_manager.py, 82, INFO, Saving data for IEX by year\n",
+      "2024-10-23 21:18:07,905, data_manager.py, 82, INFO, Saving data for IEX by year\n",
+      "2024-10-23 21:18:09,245, data_manager.py, 73, INFO, Processing ticker IDXX\n",
+      "2024-10-23 21:18:09,245, data_manager.py, 73, INFO, Processing ticker IDXX\n",
+      "2024-10-23 21:18:09,248, data_manager.py, 108, INFO, Getting stock price data for IDXX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:09,248, data_manager.py, 108, INFO, Getting stock price data for IDXX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:09,420, data_manager.py, 82, INFO, Saving data for IDXX by year\n",
+      "2024-10-23 21:18:09,420, data_manager.py, 82, INFO, Saving data for IDXX by year\n",
+      "2024-10-23 21:18:10,454, data_manager.py, 73, INFO, Processing ticker ITW\n",
+      "2024-10-23 21:18:10,454, data_manager.py, 73, INFO, Processing ticker ITW\n",
+      "2024-10-23 21:18:10,457, data_manager.py, 108, INFO, Getting stock price data for ITW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:10,457, data_manager.py, 108, INFO, Getting stock price data for ITW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:10,682, data_manager.py, 82, INFO, Saving data for ITW by year\n",
+      "2024-10-23 21:18:10,682, data_manager.py, 82, INFO, Saving data for ITW by year\n",
+      "2024-10-23 21:18:11,565, data_manager.py, 73, INFO, Processing ticker ILMN\n",
+      "2024-10-23 21:18:11,565, data_manager.py, 73, INFO, Processing ticker ILMN\n",
+      "2024-10-23 21:18:11,566, data_manager.py, 108, INFO, Getting stock price data for ILMN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:11,566, data_manager.py, 108, INFO, Getting stock price data for ILMN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:11,768, data_manager.py, 82, INFO, Saving data for ILMN by year\n",
+      "2024-10-23 21:18:11,768, data_manager.py, 82, INFO, Saving data for ILMN by year\n",
+      "2024-10-23 21:18:12,630, data_manager.py, 73, INFO, Processing ticker INCY\n",
+      "2024-10-23 21:18:12,630, data_manager.py, 73, INFO, Processing ticker INCY\n",
+      "2024-10-23 21:18:12,631, data_manager.py, 108, INFO, Getting stock price data for INCY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:12,631, data_manager.py, 108, INFO, Getting stock price data for INCY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:12,802, data_manager.py, 82, INFO, Saving data for INCY by year\n",
+      "2024-10-23 21:18:12,802, data_manager.py, 82, INFO, Saving data for INCY by year\n",
+      "2024-10-23 21:18:35,029, data_manager.py, 73, INFO, Processing ticker IR\n",
+      "2024-10-23 21:18:35,029, data_manager.py, 73, INFO, Processing ticker IR\n",
+      "2024-10-23 21:18:35,031, data_manager.py, 108, INFO, Getting stock price data for IR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:35,031, data_manager.py, 108, INFO, Getting stock price data for IR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:14,126, data_manager.py, 82, INFO, Saving data for IR by year\n",
+      "2024-10-23 21:18:14,126, data_manager.py, 82, INFO, Saving data for IR by year\n",
+      "2024-10-23 21:18:14,409, data_manager.py, 73, INFO, Processing ticker PODD\n",
+      "2024-10-23 21:18:14,409, data_manager.py, 73, INFO, Processing ticker PODD\n",
+      "2024-10-23 21:18:14,410, data_manager.py, 108, INFO, Getting stock price data for PODD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:14,410, data_manager.py, 108, INFO, Getting stock price data for PODD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:14,618, data_manager.py, 82, INFO, Saving data for PODD by year\n",
+      "2024-10-23 21:18:14,618, data_manager.py, 82, INFO, Saving data for PODD by year\n",
+      "2024-10-23 21:18:15,323, data_manager.py, 73, INFO, Processing ticker INTC\n",
+      "2024-10-23 21:18:15,323, data_manager.py, 73, INFO, Processing ticker INTC\n",
+      "2024-10-23 21:18:15,325, data_manager.py, 108, INFO, Getting stock price data for INTC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:15,325, data_manager.py, 108, INFO, Getting stock price data for INTC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:15,624, data_manager.py, 82, INFO, Saving data for INTC by year\n",
+      "2024-10-23 21:18:15,624, data_manager.py, 82, INFO, Saving data for INTC by year\n",
+      "2024-10-23 21:18:16,553, data_manager.py, 73, INFO, Processing ticker ICE\n",
+      "2024-10-23 21:18:16,553, data_manager.py, 73, INFO, Processing ticker ICE\n",
+      "2024-10-23 21:18:16,554, data_manager.py, 108, INFO, Getting stock price data for ICE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:16,554, data_manager.py, 108, INFO, Getting stock price data for ICE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:16,735, data_manager.py, 82, INFO, Saving data for ICE by year\n",
+      "2024-10-23 21:18:16,735, data_manager.py, 82, INFO, Saving data for ICE by year\n",
+      "2024-10-23 21:18:17,441, data_manager.py, 73, INFO, Processing ticker IFF\n",
+      "2024-10-23 21:18:17,441, data_manager.py, 73, INFO, Processing ticker IFF\n",
+      "2024-10-23 21:18:17,443, data_manager.py, 108, INFO, Getting stock price data for IFF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:17,443, data_manager.py, 108, INFO, Getting stock price data for IFF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:17,759, data_manager.py, 82, INFO, Saving data for IFF by year\n",
+      "2024-10-23 21:18:17,759, data_manager.py, 82, INFO, Saving data for IFF by year\n",
+      "2024-10-23 21:18:18,711, data_manager.py, 73, INFO, Processing ticker IP\n",
+      "2024-10-23 21:18:18,711, data_manager.py, 73, INFO, Processing ticker IP\n",
+      "2024-10-23 21:18:18,712, data_manager.py, 108, INFO, Getting stock price data for IP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:18,712, data_manager.py, 108, INFO, Getting stock price data for IP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:40,045, data_manager.py, 82, INFO, Saving data for IP by year\n",
+      "2024-10-23 21:18:40,045, data_manager.py, 82, INFO, Saving data for IP by year\n",
+      "2024-10-23 21:18:20,124, data_manager.py, 73, INFO, Processing ticker IPG\n",
+      "2024-10-23 21:18:20,124, data_manager.py, 73, INFO, Processing ticker IPG\n",
+      "2024-10-23 21:18:20,125, data_manager.py, 108, INFO, Getting stock price data for IPG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:20,125, data_manager.py, 108, INFO, Getting stock price data for IPG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:20,362, data_manager.py, 82, INFO, Saving data for IPG by year\n",
+      "2024-10-23 21:18:20,362, data_manager.py, 82, INFO, Saving data for IPG by year\n",
+      "2024-10-23 21:18:21,406, data_manager.py, 73, INFO, Processing ticker INTU\n",
+      "2024-10-23 21:18:21,406, data_manager.py, 73, INFO, Processing ticker INTU\n",
+      "2024-10-23 21:18:21,407, data_manager.py, 108, INFO, Getting stock price data for INTU from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:21,407, data_manager.py, 108, INFO, Getting stock price data for INTU from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:21,660, data_manager.py, 82, INFO, Saving data for INTU by year\n",
+      "2024-10-23 21:18:21,660, data_manager.py, 82, INFO, Saving data for INTU by year\n",
+      "2024-10-23 21:18:22,883, data_manager.py, 73, INFO, Processing ticker ISRG\n",
+      "2024-10-23 21:18:22,883, data_manager.py, 73, INFO, Processing ticker ISRG\n",
+      "2024-10-23 21:18:22,884, data_manager.py, 108, INFO, Getting stock price data for ISRG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:22,884, data_manager.py, 108, INFO, Getting stock price data for ISRG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:23,148, data_manager.py, 82, INFO, Saving data for ISRG by year\n",
+      "2024-10-23 21:18:23,148, data_manager.py, 82, INFO, Saving data for ISRG by year\n",
+      "2024-10-23 21:18:24,240, data_manager.py, 73, INFO, Processing ticker IVZ\n",
+      "2024-10-23 21:18:24,240, data_manager.py, 73, INFO, Processing ticker IVZ\n",
+      "2024-10-23 21:18:24,242, data_manager.py, 108, INFO, Getting stock price data for IVZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:24,242, data_manager.py, 108, INFO, Getting stock price data for IVZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:24,486, data_manager.py, 82, INFO, Saving data for IVZ by year\n",
+      "2024-10-23 21:18:24,486, data_manager.py, 82, INFO, Saving data for IVZ by year\n",
+      "2024-10-23 21:18:25,342, data_manager.py, 73, INFO, Processing ticker INVH\n",
+      "2024-10-23 21:18:25,342, data_manager.py, 73, INFO, Processing ticker INVH\n",
+      "2024-10-23 21:18:25,344, data_manager.py, 108, INFO, Getting stock price data for INVH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:25,344, data_manager.py, 108, INFO, Getting stock price data for INVH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:25,525, data_manager.py, 82, INFO, Saving data for INVH by year\n",
+      "2024-10-23 21:18:25,525, data_manager.py, 82, INFO, Saving data for INVH by year\n",
+      "2024-10-23 21:18:25,831, data_manager.py, 73, INFO, Processing ticker IQV\n",
+      "2024-10-23 21:18:25,831, data_manager.py, 73, INFO, Processing ticker IQV\n",
+      "2024-10-23 21:18:25,832, data_manager.py, 108, INFO, Getting stock price data for IQV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:25,832, data_manager.py, 108, INFO, Getting stock price data for IQV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:25,943, data_manager.py, 82, INFO, Saving data for IQV by year\n",
+      "2024-10-23 21:18:25,943, data_manager.py, 82, INFO, Saving data for IQV by year\n",
+      "2024-10-23 21:18:26,381, data_manager.py, 73, INFO, Processing ticker IRM\n",
+      "2024-10-23 21:18:26,381, data_manager.py, 73, INFO, Processing ticker IRM\n",
+      "2024-10-23 21:18:26,383, data_manager.py, 108, INFO, Getting stock price data for IRM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:26,383, data_manager.py, 108, INFO, Getting stock price data for IRM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:26,593, data_manager.py, 82, INFO, Saving data for IRM by year\n",
+      "2024-10-23 21:18:26,593, data_manager.py, 82, INFO, Saving data for IRM by year\n",
+      "2024-10-23 21:18:28,039, data_manager.py, 73, INFO, Processing ticker JBHT\n",
+      "2024-10-23 21:18:28,039, data_manager.py, 73, INFO, Processing ticker JBHT\n",
+      "2024-10-23 21:18:28,041, data_manager.py, 108, INFO, Getting stock price data for JBHT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:28,041, data_manager.py, 108, INFO, Getting stock price data for JBHT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:28,285, data_manager.py, 82, INFO, Saving data for JBHT by year\n",
+      "2024-10-23 21:18:28,285, data_manager.py, 82, INFO, Saving data for JBHT by year\n",
+      "2024-10-23 21:18:29,462, data_manager.py, 73, INFO, Processing ticker JBL\n",
+      "2024-10-23 21:18:29,462, data_manager.py, 73, INFO, Processing ticker JBL\n",
+      "2024-10-23 21:18:29,464, data_manager.py, 108, INFO, Getting stock price data for JBL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:29,464, data_manager.py, 108, INFO, Getting stock price data for JBL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:29,692, data_manager.py, 82, INFO, Saving data for JBL by year\n",
+      "2024-10-23 21:18:29,692, data_manager.py, 82, INFO, Saving data for JBL by year\n",
+      "2024-10-23 21:18:30,739, data_manager.py, 73, INFO, Processing ticker JKHY\n",
+      "2024-10-23 21:18:30,739, data_manager.py, 73, INFO, Processing ticker JKHY\n",
+      "2024-10-23 21:18:30,740, data_manager.py, 108, INFO, Getting stock price data for JKHY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:30,740, data_manager.py, 108, INFO, Getting stock price data for JKHY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:30,998, data_manager.py, 82, INFO, Saving data for JKHY by year\n",
+      "2024-10-23 21:18:30,998, data_manager.py, 82, INFO, Saving data for JKHY by year\n",
+      "2024-10-23 21:18:32,019, data_manager.py, 73, INFO, Processing ticker J\n",
+      "2024-10-23 21:18:32,019, data_manager.py, 73, INFO, Processing ticker J\n",
+      "2024-10-23 21:18:32,020, data_manager.py, 108, INFO, Getting stock price data for J from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:32,020, data_manager.py, 108, INFO, Getting stock price data for J from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:32,372, data_manager.py, 82, INFO, Saving data for J by year\n",
+      "2024-10-23 21:18:32,372, data_manager.py, 82, INFO, Saving data for J by year\n",
+      "2024-10-23 21:18:33,469, data_manager.py, 73, INFO, Processing ticker JNJ\n",
+      "2024-10-23 21:18:33,469, data_manager.py, 73, INFO, Processing ticker JNJ\n",
+      "2024-10-23 21:18:33,470, data_manager.py, 108, INFO, Getting stock price data for JNJ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:33,470, data_manager.py, 108, INFO, Getting stock price data for JNJ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:33,823, data_manager.py, 82, INFO, Saving data for JNJ by year\n",
+      "2024-10-23 21:18:33,823, data_manager.py, 82, INFO, Saving data for JNJ by year\n",
+      "2024-10-23 21:18:34,608, data_manager.py, 73, INFO, Processing ticker JCI\n",
+      "2024-10-23 21:18:34,608, data_manager.py, 73, INFO, Processing ticker JCI\n",
+      "2024-10-23 21:18:34,609, data_manager.py, 108, INFO, Getting stock price data for JCI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:34,609, data_manager.py, 108, INFO, Getting stock price data for JCI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:34,903, data_manager.py, 82, INFO, Saving data for JCI by year\n",
+      "2024-10-23 21:18:34,903, data_manager.py, 82, INFO, Saving data for JCI by year\n",
+      "2024-10-23 21:18:35,951, data_manager.py, 73, INFO, Processing ticker JPM\n",
+      "2024-10-23 21:18:35,951, data_manager.py, 73, INFO, Processing ticker JPM\n",
+      "2024-10-23 21:18:35,952, data_manager.py, 108, INFO, Getting stock price data for JPM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:35,952, data_manager.py, 108, INFO, Getting stock price data for JPM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:36,208, data_manager.py, 82, INFO, Saving data for JPM by year\n",
+      "2024-10-23 21:18:36,208, data_manager.py, 82, INFO, Saving data for JPM by year\n",
+      "2024-10-23 21:18:37,546, data_manager.py, 73, INFO, Processing ticker JNPR\n",
+      "2024-10-23 21:18:37,546, data_manager.py, 73, INFO, Processing ticker JNPR\n",
+      "2024-10-23 21:18:37,548, data_manager.py, 108, INFO, Getting stock price data for JNPR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:37,548, data_manager.py, 108, INFO, Getting stock price data for JNPR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:37,839, data_manager.py, 82, INFO, Saving data for JNPR by year\n",
+      "2024-10-23 21:18:37,839, data_manager.py, 82, INFO, Saving data for JNPR by year\n",
+      "2024-10-23 21:19:00,158, data_manager.py, 73, INFO, Processing ticker K\n",
+      "2024-10-23 21:19:00,158, data_manager.py, 73, INFO, Processing ticker K\n",
+      "2024-10-23 21:19:00,160, data_manager.py, 108, INFO, Getting stock price data for K from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:00,160, data_manager.py, 108, INFO, Getting stock price data for K from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:39,395, data_manager.py, 82, INFO, Saving data for K by year\n",
+      "2024-10-23 21:18:39,395, data_manager.py, 82, INFO, Saving data for K by year\n",
+      "2024-10-23 21:18:40,373, data_manager.py, 73, INFO, Processing ticker KVUE\n",
+      "2024-10-23 21:18:40,373, data_manager.py, 73, INFO, Processing ticker KVUE\n",
+      "2024-10-23 21:18:40,374, data_manager.py, 108, INFO, Getting stock price data for KVUE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:40,374, data_manager.py, 108, INFO, Getting stock price data for KVUE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:40,453, data_manager.py, 82, INFO, Saving data for KVUE by year\n",
+      "2024-10-23 21:18:40,453, data_manager.py, 82, INFO, Saving data for KVUE by year\n",
+      "2024-10-23 21:18:40,538, data_manager.py, 73, INFO, Processing ticker KDP\n",
+      "2024-10-23 21:18:40,538, data_manager.py, 73, INFO, Processing ticker KDP\n",
+      "2024-10-23 21:18:40,539, data_manager.py, 108, INFO, Getting stock price data for KDP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:40,539, data_manager.py, 108, INFO, Getting stock price data for KDP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:40,686, data_manager.py, 82, INFO, Saving data for KDP by year\n",
+      "2024-10-23 21:18:40,686, data_manager.py, 82, INFO, Saving data for KDP by year\n",
+      "2024-10-23 21:18:41,311, data_manager.py, 73, INFO, Processing ticker KEY\n",
+      "2024-10-23 21:18:41,311, data_manager.py, 73, INFO, Processing ticker KEY\n",
+      "2024-10-23 21:18:41,312, data_manager.py, 108, INFO, Getting stock price data for KEY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:41,312, data_manager.py, 108, INFO, Getting stock price data for KEY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:41,557, data_manager.py, 82, INFO, Saving data for KEY by year\n",
+      "2024-10-23 21:18:41,557, data_manager.py, 82, INFO, Saving data for KEY by year\n",
+      "2024-10-23 21:18:42,791, data_manager.py, 73, INFO, Processing ticker KEYS\n",
+      "2024-10-23 21:18:42,791, data_manager.py, 73, INFO, Processing ticker KEYS\n",
+      "2024-10-23 21:18:42,794, data_manager.py, 108, INFO, Getting stock price data for KEYS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:42,794, data_manager.py, 108, INFO, Getting stock price data for KEYS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:42,910, data_manager.py, 82, INFO, Saving data for KEYS by year\n",
+      "2024-10-23 21:18:42,910, data_manager.py, 82, INFO, Saving data for KEYS by year\n",
+      "2024-10-23 21:18:43,478, data_manager.py, 73, INFO, Processing ticker KMB\n",
+      "2024-10-23 21:18:43,478, data_manager.py, 73, INFO, Processing ticker KMB\n",
+      "2024-10-23 21:18:43,479, data_manager.py, 108, INFO, Getting stock price data for KMB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:43,479, data_manager.py, 108, INFO, Getting stock price data for KMB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:43,737, data_manager.py, 82, INFO, Saving data for KMB by year\n",
+      "2024-10-23 21:18:43,737, data_manager.py, 82, INFO, Saving data for KMB by year\n",
+      "2024-10-23 21:18:44,910, data_manager.py, 73, INFO, Processing ticker KIM\n",
+      "2024-10-23 21:18:44,910, data_manager.py, 73, INFO, Processing ticker KIM\n",
+      "2024-10-23 21:18:44,911, data_manager.py, 108, INFO, Getting stock price data for KIM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:44,911, data_manager.py, 108, INFO, Getting stock price data for KIM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:45,185, data_manager.py, 82, INFO, Saving data for KIM by year\n",
+      "2024-10-23 21:18:45,185, data_manager.py, 82, INFO, Saving data for KIM by year\n",
+      "2024-10-23 21:18:46,259, data_manager.py, 73, INFO, Processing ticker KMI\n",
+      "2024-10-23 21:18:46,259, data_manager.py, 73, INFO, Processing ticker KMI\n",
+      "2024-10-23 21:18:46,261, data_manager.py, 108, INFO, Getting stock price data for KMI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:46,261, data_manager.py, 108, INFO, Getting stock price data for KMI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:46,419, data_manager.py, 82, INFO, Saving data for KMI by year\n",
+      "2024-10-23 21:18:46,419, data_manager.py, 82, INFO, Saving data for KMI by year\n",
+      "2024-10-23 21:18:46,925, data_manager.py, 73, INFO, Processing ticker KLAC\n",
+      "2024-10-23 21:18:46,925, data_manager.py, 73, INFO, Processing ticker KLAC\n",
+      "2024-10-23 21:18:46,927, data_manager.py, 108, INFO, Getting stock price data for KLAC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:46,927, data_manager.py, 108, INFO, Getting stock price data for KLAC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:47,141, data_manager.py, 82, INFO, Saving data for KLAC by year\n",
+      "2024-10-23 21:18:47,141, data_manager.py, 82, INFO, Saving data for KLAC by year\n",
+      "2024-10-23 21:18:48,399, data_manager.py, 73, INFO, Processing ticker KHC\n",
+      "2024-10-23 21:18:48,399, data_manager.py, 73, INFO, Processing ticker KHC\n",
+      "2024-10-23 21:18:48,401, data_manager.py, 108, INFO, Getting stock price data for KHC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:48,401, data_manager.py, 108, INFO, Getting stock price data for KHC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:48,519, data_manager.py, 82, INFO, Saving data for KHC by year\n",
+      "2024-10-23 21:18:48,519, data_manager.py, 82, INFO, Saving data for KHC by year\n",
+      "2024-10-23 21:19:10,115, data_manager.py, 73, INFO, Processing ticker KR\n",
+      "2024-10-23 21:19:10,115, data_manager.py, 73, INFO, Processing ticker KR\n",
+      "2024-10-23 21:19:10,116, data_manager.py, 108, INFO, Getting stock price data for KR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:10,116, data_manager.py, 108, INFO, Getting stock price data for KR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:49,380, data_manager.py, 82, INFO, Saving data for KR by year\n",
+      "2024-10-23 21:18:49,380, data_manager.py, 82, INFO, Saving data for KR by year\n",
+      "2024-10-23 21:18:50,254, data_manager.py, 73, INFO, Processing ticker LHX\n",
+      "2024-10-23 21:18:50,254, data_manager.py, 73, INFO, Processing ticker LHX\n",
+      "2024-10-23 21:18:50,255, data_manager.py, 108, INFO, Getting stock price data for LHX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:50,255, data_manager.py, 108, INFO, Getting stock price data for LHX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:50,516, data_manager.py, 82, INFO, Saving data for LHX by year\n",
+      "2024-10-23 21:18:50,516, data_manager.py, 82, INFO, Saving data for LHX by year\n",
+      "2024-10-23 21:18:51,523, data_manager.py, 73, INFO, Processing ticker LH\n",
+      "2024-10-23 21:18:51,523, data_manager.py, 73, INFO, Processing ticker LH\n",
+      "2024-10-23 21:18:51,524, data_manager.py, 108, INFO, Getting stock price data for LH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:51,524, data_manager.py, 108, INFO, Getting stock price data for LH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:51,738, data_manager.py, 82, INFO, Saving data for LH by year\n",
+      "2024-10-23 21:18:51,738, data_manager.py, 82, INFO, Saving data for LH by year\n",
+      "2024-10-23 21:18:52,802, data_manager.py, 73, INFO, Processing ticker LRCX\n",
+      "2024-10-23 21:18:52,802, data_manager.py, 73, INFO, Processing ticker LRCX\n",
+      "2024-10-23 21:18:52,803, data_manager.py, 108, INFO, Getting stock price data for LRCX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:52,803, data_manager.py, 108, INFO, Getting stock price data for LRCX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:52,994, data_manager.py, 82, INFO, Saving data for LRCX by year\n",
+      "2024-10-23 21:18:52,994, data_manager.py, 82, INFO, Saving data for LRCX by year\n",
+      "2024-10-23 21:18:53,901, data_manager.py, 73, INFO, Processing ticker LW\n",
+      "2024-10-23 21:18:53,901, data_manager.py, 73, INFO, Processing ticker LW\n",
+      "2024-10-23 21:18:53,902, data_manager.py, 108, INFO, Getting stock price data for LW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:53,902, data_manager.py, 108, INFO, Getting stock price data for LW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:54,037, data_manager.py, 82, INFO, Saving data for LW by year\n",
+      "2024-10-23 21:18:54,037, data_manager.py, 82, INFO, Saving data for LW by year\n",
+      "2024-10-23 21:18:54,363, data_manager.py, 73, INFO, Processing ticker LVS\n",
+      "2024-10-23 21:18:54,363, data_manager.py, 73, INFO, Processing ticker LVS\n",
+      "2024-10-23 21:18:54,364, data_manager.py, 108, INFO, Getting stock price data for LVS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:54,364, data_manager.py, 108, INFO, Getting stock price data for LVS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:54,569, data_manager.py, 82, INFO, Saving data for LVS by year\n",
+      "2024-10-23 21:18:54,569, data_manager.py, 82, INFO, Saving data for LVS by year\n",
+      "2024-10-23 21:18:55,371, data_manager.py, 73, INFO, Processing ticker LDOS\n",
+      "2024-10-23 21:18:55,371, data_manager.py, 73, INFO, Processing ticker LDOS\n",
+      "2024-10-23 21:18:55,372, data_manager.py, 108, INFO, Getting stock price data for LDOS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:55,372, data_manager.py, 108, INFO, Getting stock price data for LDOS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:55,552, data_manager.py, 82, INFO, Saving data for LDOS by year\n",
+      "2024-10-23 21:18:55,552, data_manager.py, 82, INFO, Saving data for LDOS by year\n",
+      "2024-10-23 21:18:56,260, data_manager.py, 73, INFO, Processing ticker LEN\n",
+      "2024-10-23 21:18:56,260, data_manager.py, 73, INFO, Processing ticker LEN\n",
+      "2024-10-23 21:18:56,261, data_manager.py, 108, INFO, Getting stock price data for LEN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:56,261, data_manager.py, 108, INFO, Getting stock price data for LEN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:56,550, data_manager.py, 82, INFO, Saving data for LEN by year\n",
+      "2024-10-23 21:18:56,550, data_manager.py, 82, INFO, Saving data for LEN by year\n",
+      "2024-10-23 21:18:57,656, data_manager.py, 73, INFO, Processing ticker LIN\n",
+      "2024-10-23 21:18:57,656, data_manager.py, 73, INFO, Processing ticker LIN\n",
+      "2024-10-23 21:18:57,657, data_manager.py, 108, INFO, Getting stock price data for LIN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:57,657, data_manager.py, 108, INFO, Getting stock price data for LIN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:57,884, data_manager.py, 82, INFO, Saving data for LIN by year\n",
+      "2024-10-23 21:18:57,884, data_manager.py, 82, INFO, Saving data for LIN by year\n",
+      "2024-10-23 21:18:58,773, data_manager.py, 73, INFO, Processing ticker LYV\n",
+      "2024-10-23 21:18:58,773, data_manager.py, 73, INFO, Processing ticker LYV\n",
+      "2024-10-23 21:18:58,774, data_manager.py, 108, INFO, Getting stock price data for LYV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:58,774, data_manager.py, 108, INFO, Getting stock price data for LYV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:58,907, data_manager.py, 82, INFO, Saving data for LYV by year\n",
+      "2024-10-23 21:18:58,907, data_manager.py, 82, INFO, Saving data for LYV by year\n",
+      "2024-10-23 21:18:59,632, data_manager.py, 73, INFO, Processing ticker LKQ\n",
+      "2024-10-23 21:18:59,632, data_manager.py, 73, INFO, Processing ticker LKQ\n",
+      "2024-10-23 21:18:59,634, data_manager.py, 108, INFO, Getting stock price data for LKQ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:18:59,634, data_manager.py, 108, INFO, Getting stock price data for LKQ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:18:59,841, data_manager.py, 82, INFO, Saving data for LKQ by year\n",
+      "2024-10-23 21:18:59,841, data_manager.py, 82, INFO, Saving data for LKQ by year\n",
+      "2024-10-23 21:19:00,727, data_manager.py, 73, INFO, Processing ticker LMT\n",
+      "2024-10-23 21:19:00,727, data_manager.py, 73, INFO, Processing ticker LMT\n",
+      "2024-10-23 21:19:00,728, data_manager.py, 108, INFO, Getting stock price data for LMT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:00,728, data_manager.py, 108, INFO, Getting stock price data for LMT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:00,928, data_manager.py, 82, INFO, Saving data for LMT by year\n",
+      "2024-10-23 21:19:00,928, data_manager.py, 82, INFO, Saving data for LMT by year\n",
+      "2024-10-23 21:19:01,952, data_manager.py, 73, INFO, Processing ticker L\n",
+      "2024-10-23 21:19:01,952, data_manager.py, 73, INFO, Processing ticker L\n",
+      "2024-10-23 21:19:01,953, data_manager.py, 108, INFO, Getting stock price data for L from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:01,953, data_manager.py, 108, INFO, Getting stock price data for L from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:02,317, data_manager.py, 82, INFO, Saving data for L by year\n",
+      "2024-10-23 21:19:02,317, data_manager.py, 82, INFO, Saving data for L by year\n",
+      "2024-10-23 21:19:03,286, data_manager.py, 73, INFO, Processing ticker LOW\n",
+      "2024-10-23 21:19:03,286, data_manager.py, 73, INFO, Processing ticker LOW\n",
+      "2024-10-23 21:19:03,287, data_manager.py, 108, INFO, Getting stock price data for LOW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:03,287, data_manager.py, 108, INFO, Getting stock price data for LOW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:03,502, data_manager.py, 82, INFO, Saving data for LOW by year\n",
+      "2024-10-23 21:19:03,502, data_manager.py, 82, INFO, Saving data for LOW by year\n",
+      "2024-10-23 21:19:04,396, data_manager.py, 73, INFO, Processing ticker LULU\n",
+      "2024-10-23 21:19:04,396, data_manager.py, 73, INFO, Processing ticker LULU\n",
+      "2024-10-23 21:19:04,397, data_manager.py, 108, INFO, Getting stock price data for LULU from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:04,397, data_manager.py, 108, INFO, Getting stock price data for LULU from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:04,546, data_manager.py, 82, INFO, Saving data for LULU by year\n",
+      "2024-10-23 21:19:04,546, data_manager.py, 82, INFO, Saving data for LULU by year\n",
+      "2024-10-23 21:19:05,288, data_manager.py, 73, INFO, Processing ticker LYB\n",
+      "2024-10-23 21:19:05,288, data_manager.py, 73, INFO, Processing ticker LYB\n",
+      "2024-10-23 21:19:05,289, data_manager.py, 108, INFO, Getting stock price data for LYB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:05,289, data_manager.py, 108, INFO, Getting stock price data for LYB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:05,470, data_manager.py, 82, INFO, Saving data for LYB by year\n",
+      "2024-10-23 21:19:05,470, data_manager.py, 82, INFO, Saving data for LYB by year\n",
+      "2024-10-23 21:19:05,991, data_manager.py, 73, INFO, Processing ticker MTB\n",
+      "2024-10-23 21:19:05,991, data_manager.py, 73, INFO, Processing ticker MTB\n",
+      "2024-10-23 21:19:05,992, data_manager.py, 108, INFO, Getting stock price data for MTB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:05,992, data_manager.py, 108, INFO, Getting stock price data for MTB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:06,337, data_manager.py, 82, INFO, Saving data for MTB by year\n",
+      "2024-10-23 21:19:06,337, data_manager.py, 82, INFO, Saving data for MTB by year\n",
+      "2024-10-23 21:19:07,264, data_manager.py, 73, INFO, Processing ticker MRO\n",
+      "2024-10-23 21:19:07,264, data_manager.py, 73, INFO, Processing ticker MRO\n",
+      "2024-10-23 21:19:07,266, data_manager.py, 108, INFO, Getting stock price data for MRO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:07,266, data_manager.py, 108, INFO, Getting stock price data for MRO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:07,568, data_manager.py, 82, INFO, Saving data for MRO by year\n",
+      "2024-10-23 21:19:07,568, data_manager.py, 82, INFO, Saving data for MRO by year\n",
+      "2024-10-23 21:19:08,722, data_manager.py, 73, INFO, Processing ticker MPC\n",
+      "2024-10-23 21:19:08,722, data_manager.py, 73, INFO, Processing ticker MPC\n",
+      "2024-10-23 21:19:08,723, data_manager.py, 108, INFO, Getting stock price data for MPC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:08,723, data_manager.py, 108, INFO, Getting stock price data for MPC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:08,871, data_manager.py, 82, INFO, Saving data for MPC by year\n",
+      "2024-10-23 21:19:08,871, data_manager.py, 82, INFO, Saving data for MPC by year\n",
+      "2024-10-23 21:19:09,355, data_manager.py, 73, INFO, Processing ticker MKTX\n",
+      "2024-10-23 21:19:09,355, data_manager.py, 73, INFO, Processing ticker MKTX\n",
+      "2024-10-23 21:19:09,358, data_manager.py, 108, INFO, Getting stock price data for MKTX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:09,358, data_manager.py, 108, INFO, Getting stock price data for MKTX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:09,533, data_manager.py, 82, INFO, Saving data for MKTX by year\n",
+      "2024-10-23 21:19:09,533, data_manager.py, 82, INFO, Saving data for MKTX by year\n",
+      "2024-10-23 21:19:10,361, data_manager.py, 73, INFO, Processing ticker MAR\n",
+      "2024-10-23 21:19:10,361, data_manager.py, 73, INFO, Processing ticker MAR\n",
+      "2024-10-23 21:19:10,362, data_manager.py, 108, INFO, Getting stock price data for MAR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:10,362, data_manager.py, 108, INFO, Getting stock price data for MAR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:10,662, data_manager.py, 82, INFO, Saving data for MAR by year\n",
+      "2024-10-23 21:19:10,662, data_manager.py, 82, INFO, Saving data for MAR by year\n",
+      "2024-10-23 21:19:11,550, data_manager.py, 73, INFO, Processing ticker MMC\n",
+      "2024-10-23 21:19:11,550, data_manager.py, 73, INFO, Processing ticker MMC\n",
+      "2024-10-23 21:19:11,551, data_manager.py, 108, INFO, Getting stock price data for MMC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:11,551, data_manager.py, 108, INFO, Getting stock price data for MMC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:11,903, data_manager.py, 82, INFO, Saving data for MMC by year\n",
+      "2024-10-23 21:19:11,903, data_manager.py, 82, INFO, Saving data for MMC by year\n",
+      "2024-10-23 21:19:12,724, data_manager.py, 73, INFO, Processing ticker MLM\n",
+      "2024-10-23 21:19:12,724, data_manager.py, 73, INFO, Processing ticker MLM\n",
+      "2024-10-23 21:19:12,725, data_manager.py, 108, INFO, Getting stock price data for MLM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:12,725, data_manager.py, 108, INFO, Getting stock price data for MLM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:12,990, data_manager.py, 82, INFO, Saving data for MLM by year\n",
+      "2024-10-23 21:19:12,990, data_manager.py, 82, INFO, Saving data for MLM by year\n",
+      "2024-10-23 21:19:13,810, data_manager.py, 73, INFO, Processing ticker MAS\n",
+      "2024-10-23 21:19:13,810, data_manager.py, 73, INFO, Processing ticker MAS\n",
+      "2024-10-23 21:19:13,811, data_manager.py, 108, INFO, Getting stock price data for MAS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:13,811, data_manager.py, 108, INFO, Getting stock price data for MAS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:14,110, data_manager.py, 82, INFO, Saving data for MAS by year\n",
+      "2024-10-23 21:19:14,110, data_manager.py, 82, INFO, Saving data for MAS by year\n",
+      "2024-10-23 21:19:14,956, data_manager.py, 73, INFO, Processing ticker MA\n",
+      "2024-10-23 21:19:14,956, data_manager.py, 73, INFO, Processing ticker MA\n",
+      "2024-10-23 21:19:14,958, data_manager.py, 108, INFO, Getting stock price data for MA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:14,958, data_manager.py, 108, INFO, Getting stock price data for MA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:15,164, data_manager.py, 82, INFO, Saving data for MA by year\n",
+      "2024-10-23 21:19:15,164, data_manager.py, 82, INFO, Saving data for MA by year\n",
+      "2024-10-23 21:19:15,788, data_manager.py, 73, INFO, Processing ticker MTCH\n",
+      "2024-10-23 21:19:15,788, data_manager.py, 73, INFO, Processing ticker MTCH\n",
+      "2024-10-23 21:19:15,789, data_manager.py, 108, INFO, Getting stock price data for MTCH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:15,789, data_manager.py, 108, INFO, Getting stock price data for MTCH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:16,122, data_manager.py, 82, INFO, Saving data for MTCH by year\n",
+      "2024-10-23 21:19:16,122, data_manager.py, 82, INFO, Saving data for MTCH by year\n",
+      "2024-10-23 21:19:17,163, data_manager.py, 73, INFO, Processing ticker MKC\n",
+      "2024-10-23 21:19:17,163, data_manager.py, 73, INFO, Processing ticker MKC\n",
+      "2024-10-23 21:19:17,164, data_manager.py, 108, INFO, Getting stock price data for MKC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:17,164, data_manager.py, 108, INFO, Getting stock price data for MKC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:17,407, data_manager.py, 82, INFO, Saving data for MKC by year\n",
+      "2024-10-23 21:19:17,407, data_manager.py, 82, INFO, Saving data for MKC by year\n",
+      "2024-10-23 21:19:18,238, data_manager.py, 73, INFO, Processing ticker MCD\n",
+      "2024-10-23 21:19:18,238, data_manager.py, 73, INFO, Processing ticker MCD\n",
+      "2024-10-23 21:19:18,240, data_manager.py, 108, INFO, Getting stock price data for MCD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:18,240, data_manager.py, 108, INFO, Getting stock price data for MCD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:18,526, data_manager.py, 82, INFO, Saving data for MCD by year\n",
+      "2024-10-23 21:19:18,526, data_manager.py, 82, INFO, Saving data for MCD by year\n",
+      "2024-10-23 21:19:40,511, data_manager.py, 73, INFO, Processing ticker MCK\n",
+      "2024-10-23 21:19:40,511, data_manager.py, 73, INFO, Processing ticker MCK\n",
+      "2024-10-23 21:19:40,512, data_manager.py, 108, INFO, Getting stock price data for MCK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:40,512, data_manager.py, 108, INFO, Getting stock price data for MCK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:19,682, data_manager.py, 82, INFO, Saving data for MCK by year\n",
+      "2024-10-23 21:19:19,682, data_manager.py, 82, INFO, Saving data for MCK by year\n",
+      "2024-10-23 21:19:20,522, data_manager.py, 73, INFO, Processing ticker MDT\n",
+      "2024-10-23 21:19:20,522, data_manager.py, 73, INFO, Processing ticker MDT\n",
+      "2024-10-23 21:19:20,524, data_manager.py, 108, INFO, Getting stock price data for MDT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:20,524, data_manager.py, 108, INFO, Getting stock price data for MDT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:20,811, data_manager.py, 82, INFO, Saving data for MDT by year\n",
+      "2024-10-23 21:19:20,811, data_manager.py, 82, INFO, Saving data for MDT by year\n",
+      "2024-10-23 21:19:21,925, data_manager.py, 73, INFO, Processing ticker MRK\n",
+      "2024-10-23 21:19:21,925, data_manager.py, 73, INFO, Processing ticker MRK\n",
+      "2024-10-23 21:19:21,927, data_manager.py, 108, INFO, Getting stock price data for MRK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:21,927, data_manager.py, 108, INFO, Getting stock price data for MRK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:22,194, data_manager.py, 82, INFO, Saving data for MRK by year\n",
+      "2024-10-23 21:19:22,194, data_manager.py, 82, INFO, Saving data for MRK by year\n",
+      "2024-10-23 21:19:23,023, data_manager.py, 73, INFO, Processing ticker META\n",
+      "2024-10-23 21:19:23,023, data_manager.py, 73, INFO, Processing ticker META\n",
+      "2024-10-23 21:19:23,024, data_manager.py, 108, INFO, Getting stock price data for META from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:23,024, data_manager.py, 108, INFO, Getting stock price data for META from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:23,153, data_manager.py, 82, INFO, Saving data for META by year\n",
+      "2024-10-23 21:19:23,153, data_manager.py, 82, INFO, Saving data for META by year\n",
+      "2024-10-23 21:19:23,576, data_manager.py, 73, INFO, Processing ticker MET\n",
+      "2024-10-23 21:19:23,576, data_manager.py, 73, INFO, Processing ticker MET\n",
+      "2024-10-23 21:19:23,579, data_manager.py, 108, INFO, Getting stock price data for MET from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:23,579, data_manager.py, 108, INFO, Getting stock price data for MET from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:23,779, data_manager.py, 82, INFO, Saving data for MET by year\n",
+      "2024-10-23 21:19:23,779, data_manager.py, 82, INFO, Saving data for MET by year\n",
+      "2024-10-23 21:19:24,617, data_manager.py, 73, INFO, Processing ticker MTD\n",
+      "2024-10-23 21:19:24,617, data_manager.py, 73, INFO, Processing ticker MTD\n",
+      "2024-10-23 21:19:24,618, data_manager.py, 108, INFO, Getting stock price data for MTD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:24,618, data_manager.py, 108, INFO, Getting stock price data for MTD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:24,822, data_manager.py, 82, INFO, Saving data for MTD by year\n",
+      "2024-10-23 21:19:24,822, data_manager.py, 82, INFO, Saving data for MTD by year\n",
+      "2024-10-23 21:19:26,032, data_manager.py, 73, INFO, Processing ticker MGM\n",
+      "2024-10-23 21:19:26,032, data_manager.py, 73, INFO, Processing ticker MGM\n",
+      "2024-10-23 21:19:26,033, data_manager.py, 108, INFO, Getting stock price data for MGM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:26,033, data_manager.py, 108, INFO, Getting stock price data for MGM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:26,319, data_manager.py, 82, INFO, Saving data for MGM by year\n",
+      "2024-10-23 21:19:26,319, data_manager.py, 82, INFO, Saving data for MGM by year\n",
+      "2024-10-23 21:19:27,140, data_manager.py, 73, INFO, Processing ticker MCHP\n",
+      "2024-10-23 21:19:27,140, data_manager.py, 73, INFO, Processing ticker MCHP\n",
+      "2024-10-23 21:19:27,141, data_manager.py, 108, INFO, Getting stock price data for MCHP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:27,141, data_manager.py, 108, INFO, Getting stock price data for MCHP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:27,360, data_manager.py, 82, INFO, Saving data for MCHP by year\n",
+      "2024-10-23 21:19:27,360, data_manager.py, 82, INFO, Saving data for MCHP by year\n",
+      "2024-10-23 21:19:28,190, data_manager.py, 73, INFO, Processing ticker MU\n",
+      "2024-10-23 21:19:28,190, data_manager.py, 73, INFO, Processing ticker MU\n",
+      "2024-10-23 21:19:28,191, data_manager.py, 108, INFO, Getting stock price data for MU from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:28,191, data_manager.py, 108, INFO, Getting stock price data for MU from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:28,397, data_manager.py, 82, INFO, Saving data for MU by year\n",
+      "2024-10-23 21:19:28,397, data_manager.py, 82, INFO, Saving data for MU by year\n",
+      "2024-10-23 21:19:29,403, data_manager.py, 73, INFO, Processing ticker MSFT\n",
+      "2024-10-23 21:19:29,403, data_manager.py, 73, INFO, Processing ticker MSFT\n",
+      "2024-10-23 21:19:29,405, data_manager.py, 108, INFO, Getting stock price data for MSFT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:29,405, data_manager.py, 108, INFO, Getting stock price data for MSFT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:50,619, data_manager.py, 82, INFO, Saving data for MSFT by year\n",
+      "2024-10-23 21:19:50,619, data_manager.py, 82, INFO, Saving data for MSFT by year\n",
+      "2024-10-23 21:19:30,533, data_manager.py, 73, INFO, Processing ticker MAA\n",
+      "2024-10-23 21:19:30,533, data_manager.py, 73, INFO, Processing ticker MAA\n",
+      "2024-10-23 21:19:30,534, data_manager.py, 108, INFO, Getting stock price data for MAA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:30,534, data_manager.py, 108, INFO, Getting stock price data for MAA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:30,817, data_manager.py, 82, INFO, Saving data for MAA by year\n",
+      "2024-10-23 21:19:30,817, data_manager.py, 82, INFO, Saving data for MAA by year\n",
+      "2024-10-23 21:19:31,740, data_manager.py, 73, INFO, Processing ticker MRNA\n",
+      "2024-10-23 21:19:31,740, data_manager.py, 73, INFO, Processing ticker MRNA\n",
+      "2024-10-23 21:19:31,744, data_manager.py, 108, INFO, Getting stock price data for MRNA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:31,744, data_manager.py, 108, INFO, Getting stock price data for MRNA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:31,851, data_manager.py, 82, INFO, Saving data for MRNA by year\n",
+      "2024-10-23 21:19:31,851, data_manager.py, 82, INFO, Saving data for MRNA by year\n",
+      "2024-10-23 21:19:32,147, data_manager.py, 73, INFO, Processing ticker MHK\n",
+      "2024-10-23 21:19:32,147, data_manager.py, 73, INFO, Processing ticker MHK\n",
+      "2024-10-23 21:19:32,148, data_manager.py, 108, INFO, Getting stock price data for MHK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:32,148, data_manager.py, 108, INFO, Getting stock price data for MHK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:32,316, data_manager.py, 82, INFO, Saving data for MHK by year\n",
+      "2024-10-23 21:19:32,316, data_manager.py, 82, INFO, Saving data for MHK by year\n",
+      "2024-10-23 21:19:33,374, data_manager.py, 73, INFO, Processing ticker MOH\n",
+      "2024-10-23 21:19:33,374, data_manager.py, 73, INFO, Processing ticker MOH\n",
+      "2024-10-23 21:19:33,376, data_manager.py, 108, INFO, Getting stock price data for MOH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:33,376, data_manager.py, 108, INFO, Getting stock price data for MOH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:33,660, data_manager.py, 82, INFO, Saving data for MOH by year\n",
+      "2024-10-23 21:19:33,660, data_manager.py, 82, INFO, Saving data for MOH by year\n",
+      "2024-10-23 21:19:34,454, data_manager.py, 73, INFO, Processing ticker TAP\n",
+      "2024-10-23 21:19:34,454, data_manager.py, 73, INFO, Processing ticker TAP\n",
+      "2024-10-23 21:19:34,455, data_manager.py, 108, INFO, Getting stock price data for TAP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:34,455, data_manager.py, 108, INFO, Getting stock price data for TAP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:34,691, data_manager.py, 82, INFO, Saving data for TAP by year\n",
+      "2024-10-23 21:19:34,691, data_manager.py, 82, INFO, Saving data for TAP by year\n",
+      "2024-10-23 21:19:35,503, data_manager.py, 73, INFO, Processing ticker MDLZ\n",
+      "2024-10-23 21:19:35,503, data_manager.py, 73, INFO, Processing ticker MDLZ\n",
+      "2024-10-23 21:19:35,504, data_manager.py, 108, INFO, Getting stock price data for MDLZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:35,504, data_manager.py, 108, INFO, Getting stock price data for MDLZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:35,687, data_manager.py, 82, INFO, Saving data for MDLZ by year\n",
+      "2024-10-23 21:19:35,687, data_manager.py, 82, INFO, Saving data for MDLZ by year\n",
+      "2024-10-23 21:19:36,602, data_manager.py, 73, INFO, Processing ticker MPWR\n",
+      "2024-10-23 21:19:36,602, data_manager.py, 73, INFO, Processing ticker MPWR\n",
+      "2024-10-23 21:19:36,603, data_manager.py, 108, INFO, Getting stock price data for MPWR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:36,603, data_manager.py, 108, INFO, Getting stock price data for MPWR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:36,790, data_manager.py, 82, INFO, Saving data for MPWR by year\n",
+      "2024-10-23 21:19:36,790, data_manager.py, 82, INFO, Saving data for MPWR by year\n",
+      "2024-10-23 21:19:37,580, data_manager.py, 73, INFO, Processing ticker MNST\n",
+      "2024-10-23 21:19:37,580, data_manager.py, 73, INFO, Processing ticker MNST\n",
+      "2024-10-23 21:19:37,582, data_manager.py, 108, INFO, Getting stock price data for MNST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:37,582, data_manager.py, 108, INFO, Getting stock price data for MNST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:37,775, data_manager.py, 82, INFO, Saving data for MNST by year\n",
+      "2024-10-23 21:19:37,775, data_manager.py, 82, INFO, Saving data for MNST by year\n",
+      "2024-10-23 21:19:39,142, data_manager.py, 73, INFO, Processing ticker MCO\n",
+      "2024-10-23 21:19:39,142, data_manager.py, 73, INFO, Processing ticker MCO\n",
+      "2024-10-23 21:19:39,144, data_manager.py, 108, INFO, Getting stock price data for MCO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:39,144, data_manager.py, 108, INFO, Getting stock price data for MCO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:39,487, data_manager.py, 82, INFO, Saving data for MCO by year\n",
+      "2024-10-23 21:19:39,487, data_manager.py, 82, INFO, Saving data for MCO by year\n",
+      "2024-10-23 21:19:40,308, data_manager.py, 73, INFO, Processing ticker MS\n",
+      "2024-10-23 21:19:40,308, data_manager.py, 73, INFO, Processing ticker MS\n",
+      "2024-10-23 21:19:40,310, data_manager.py, 108, INFO, Getting stock price data for MS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:40,310, data_manager.py, 108, INFO, Getting stock price data for MS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:40,549, data_manager.py, 82, INFO, Saving data for MS by year\n",
+      "2024-10-23 21:19:40,549, data_manager.py, 82, INFO, Saving data for MS by year\n",
+      "2024-10-23 21:19:41,626, data_manager.py, 73, INFO, Processing ticker MOS\n",
+      "2024-10-23 21:19:41,626, data_manager.py, 73, INFO, Processing ticker MOS\n",
+      "2024-10-23 21:19:41,629, data_manager.py, 108, INFO, Getting stock price data for MOS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:41,629, data_manager.py, 108, INFO, Getting stock price data for MOS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:41,969, data_manager.py, 82, INFO, Saving data for MOS by year\n",
+      "2024-10-23 21:19:41,969, data_manager.py, 82, INFO, Saving data for MOS by year\n",
+      "2024-10-23 21:19:43,212, data_manager.py, 73, INFO, Processing ticker MSI\n",
+      "2024-10-23 21:19:43,212, data_manager.py, 73, INFO, Processing ticker MSI\n",
+      "2024-10-23 21:19:43,213, data_manager.py, 108, INFO, Getting stock price data for MSI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:43,213, data_manager.py, 108, INFO, Getting stock price data for MSI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:43,531, data_manager.py, 82, INFO, Saving data for MSI by year\n",
+      "2024-10-23 21:19:43,531, data_manager.py, 82, INFO, Saving data for MSI by year\n",
+      "2024-10-23 21:19:44,578, data_manager.py, 73, INFO, Processing ticker MSCI\n",
+      "2024-10-23 21:19:44,578, data_manager.py, 73, INFO, Processing ticker MSCI\n",
+      "2024-10-23 21:19:44,579, data_manager.py, 108, INFO, Getting stock price data for MSCI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:44,579, data_manager.py, 108, INFO, Getting stock price data for MSCI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:44,752, data_manager.py, 82, INFO, Saving data for MSCI by year\n",
+      "2024-10-23 21:19:44,752, data_manager.py, 82, INFO, Saving data for MSCI by year\n",
+      "2024-10-23 21:19:45,405, data_manager.py, 73, INFO, Processing ticker NDAQ\n",
+      "2024-10-23 21:19:45,405, data_manager.py, 73, INFO, Processing ticker NDAQ\n",
+      "2024-10-23 21:19:45,407, data_manager.py, 108, INFO, Getting stock price data for NDAQ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:45,407, data_manager.py, 108, INFO, Getting stock price data for NDAQ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:45,617, data_manager.py, 82, INFO, Saving data for NDAQ by year\n",
+      "2024-10-23 21:19:45,617, data_manager.py, 82, INFO, Saving data for NDAQ by year\n",
+      "2024-10-23 21:19:46,687, data_manager.py, 73, INFO, Processing ticker NTAP\n",
+      "2024-10-23 21:19:46,687, data_manager.py, 73, INFO, Processing ticker NTAP\n",
+      "2024-10-23 21:19:46,688, data_manager.py, 108, INFO, Getting stock price data for NTAP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:46,688, data_manager.py, 108, INFO, Getting stock price data for NTAP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:46,913, data_manager.py, 82, INFO, Saving data for NTAP by year\n",
+      "2024-10-23 21:19:46,913, data_manager.py, 82, INFO, Saving data for NTAP by year\n",
+      "2024-10-23 21:19:48,277, data_manager.py, 73, INFO, Processing ticker NFLX\n",
+      "2024-10-23 21:19:48,277, data_manager.py, 73, INFO, Processing ticker NFLX\n",
+      "2024-10-23 21:19:48,278, data_manager.py, 108, INFO, Getting stock price data for NFLX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:48,278, data_manager.py, 108, INFO, Getting stock price data for NFLX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:48,768, data_manager.py, 82, INFO, Saving data for NFLX by year\n",
+      "2024-10-23 21:19:48,768, data_manager.py, 82, INFO, Saving data for NFLX by year\n",
+      "2024-10-23 21:19:49,919, data_manager.py, 73, INFO, Processing ticker NEM\n",
+      "2024-10-23 21:19:49,919, data_manager.py, 73, INFO, Processing ticker NEM\n",
+      "2024-10-23 21:19:49,920, data_manager.py, 108, INFO, Getting stock price data for NEM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:49,920, data_manager.py, 108, INFO, Getting stock price data for NEM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:11,237, data_manager.py, 82, INFO, Saving data for NEM by year\n",
+      "2024-10-23 21:20:11,237, data_manager.py, 82, INFO, Saving data for NEM by year\n",
+      "2024-10-23 21:19:51,126, data_manager.py, 73, INFO, Processing ticker NWSA\n",
+      "2024-10-23 21:19:51,126, data_manager.py, 73, INFO, Processing ticker NWSA\n",
+      "2024-10-23 21:19:51,128, data_manager.py, 108, INFO, Getting stock price data for NWSA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:51,128, data_manager.py, 108, INFO, Getting stock price data for NWSA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:51,387, data_manager.py, 82, INFO, Saving data for NWSA by year\n",
+      "2024-10-23 21:19:51,387, data_manager.py, 82, INFO, Saving data for NWSA by year\n",
+      "2024-10-23 21:19:51,855, data_manager.py, 73, INFO, Processing ticker NWS\n",
+      "2024-10-23 21:19:51,855, data_manager.py, 73, INFO, Processing ticker NWS\n",
+      "2024-10-23 21:19:51,856, data_manager.py, 108, INFO, Getting stock price data for NWS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:51,856, data_manager.py, 108, INFO, Getting stock price data for NWS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:52,056, data_manager.py, 82, INFO, Saving data for NWS by year\n",
+      "2024-10-23 21:19:52,056, data_manager.py, 82, INFO, Saving data for NWS by year\n",
+      "2024-10-23 21:19:52,541, data_manager.py, 73, INFO, Processing ticker NEE\n",
+      "2024-10-23 21:19:52,541, data_manager.py, 73, INFO, Processing ticker NEE\n",
+      "2024-10-23 21:19:52,543, data_manager.py, 108, INFO, Getting stock price data for NEE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:52,543, data_manager.py, 108, INFO, Getting stock price data for NEE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:52,822, data_manager.py, 82, INFO, Saving data for NEE by year\n",
+      "2024-10-23 21:19:52,822, data_manager.py, 82, INFO, Saving data for NEE by year\n",
+      "2024-10-23 21:19:54,071, data_manager.py, 73, INFO, Processing ticker NKE\n",
+      "2024-10-23 21:19:54,071, data_manager.py, 73, INFO, Processing ticker NKE\n",
+      "2024-10-23 21:19:54,073, data_manager.py, 108, INFO, Getting stock price data for NKE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:54,073, data_manager.py, 108, INFO, Getting stock price data for NKE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:54,346, data_manager.py, 82, INFO, Saving data for NKE by year\n",
+      "2024-10-23 21:19:54,346, data_manager.py, 82, INFO, Saving data for NKE by year\n",
+      "2024-10-23 21:19:55,297, data_manager.py, 73, INFO, Processing ticker NI\n",
+      "2024-10-23 21:19:55,297, data_manager.py, 73, INFO, Processing ticker NI\n",
+      "2024-10-23 21:19:55,299, data_manager.py, 108, INFO, Getting stock price data for NI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:55,299, data_manager.py, 108, INFO, Getting stock price data for NI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:55,630, data_manager.py, 82, INFO, Saving data for NI by year\n",
+      "2024-10-23 21:19:55,630, data_manager.py, 82, INFO, Saving data for NI by year\n",
+      "2024-10-23 21:19:56,503, data_manager.py, 73, INFO, Processing ticker NDSN\n",
+      "2024-10-23 21:19:56,503, data_manager.py, 73, INFO, Processing ticker NDSN\n",
+      "2024-10-23 21:19:56,505, data_manager.py, 108, INFO, Getting stock price data for NDSN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:56,505, data_manager.py, 108, INFO, Getting stock price data for NDSN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:56,785, data_manager.py, 82, INFO, Saving data for NDSN by year\n",
+      "2024-10-23 21:19:56,785, data_manager.py, 82, INFO, Saving data for NDSN by year\n",
+      "2024-10-23 21:19:57,623, data_manager.py, 73, INFO, Processing ticker NSC\n",
+      "2024-10-23 21:19:57,623, data_manager.py, 73, INFO, Processing ticker NSC\n",
+      "2024-10-23 21:19:57,625, data_manager.py, 108, INFO, Getting stock price data for NSC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:57,625, data_manager.py, 108, INFO, Getting stock price data for NSC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:57,908, data_manager.py, 82, INFO, Saving data for NSC by year\n",
+      "2024-10-23 21:19:57,908, data_manager.py, 82, INFO, Saving data for NSC by year\n",
+      "2024-10-23 21:19:58,905, data_manager.py, 73, INFO, Processing ticker NTRS\n",
+      "2024-10-23 21:19:58,905, data_manager.py, 73, INFO, Processing ticker NTRS\n",
+      "2024-10-23 21:19:58,906, data_manager.py, 108, INFO, Getting stock price data for NTRS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:19:58,906, data_manager.py, 108, INFO, Getting stock price data for NTRS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:19:59,289, data_manager.py, 82, INFO, Saving data for NTRS by year\n",
+      "2024-10-23 21:19:59,289, data_manager.py, 82, INFO, Saving data for NTRS by year\n",
+      "2024-10-23 21:20:00,255, data_manager.py, 73, INFO, Processing ticker NOC\n",
+      "2024-10-23 21:20:00,255, data_manager.py, 73, INFO, Processing ticker NOC\n",
+      "2024-10-23 21:20:00,256, data_manager.py, 108, INFO, Getting stock price data for NOC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:00,256, data_manager.py, 108, INFO, Getting stock price data for NOC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:00,560, data_manager.py, 82, INFO, Saving data for NOC by year\n",
+      "2024-10-23 21:20:00,560, data_manager.py, 82, INFO, Saving data for NOC by year\n",
+      "2024-10-23 21:20:01,533, data_manager.py, 73, INFO, Processing ticker NCLH\n",
+      "2024-10-23 21:20:01,533, data_manager.py, 73, INFO, Processing ticker NCLH\n",
+      "2024-10-23 21:20:01,535, data_manager.py, 108, INFO, Getting stock price data for NCLH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:01,535, data_manager.py, 108, INFO, Getting stock price data for NCLH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:01,664, data_manager.py, 82, INFO, Saving data for NCLH by year\n",
+      "2024-10-23 21:20:01,664, data_manager.py, 82, INFO, Saving data for NCLH by year\n",
+      "2024-10-23 21:20:02,100, data_manager.py, 73, INFO, Processing ticker NRG\n",
+      "2024-10-23 21:20:02,100, data_manager.py, 73, INFO, Processing ticker NRG\n",
+      "2024-10-23 21:20:02,102, data_manager.py, 108, INFO, Getting stock price data for NRG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:02,102, data_manager.py, 108, INFO, Getting stock price data for NRG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:02,327, data_manager.py, 82, INFO, Saving data for NRG by year\n",
+      "2024-10-23 21:20:02,327, data_manager.py, 82, INFO, Saving data for NRG by year\n",
+      "2024-10-23 21:20:03,184, data_manager.py, 73, INFO, Processing ticker NUE\n",
+      "2024-10-23 21:20:03,184, data_manager.py, 73, INFO, Processing ticker NUE\n",
+      "2024-10-23 21:20:03,186, data_manager.py, 108, INFO, Getting stock price data for NUE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:03,186, data_manager.py, 108, INFO, Getting stock price data for NUE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:03,455, data_manager.py, 82, INFO, Saving data for NUE by year\n",
+      "2024-10-23 21:20:03,455, data_manager.py, 82, INFO, Saving data for NUE by year\n",
+      "2024-10-23 21:20:04,372, data_manager.py, 73, INFO, Processing ticker NVDA\n",
+      "2024-10-23 21:20:04,372, data_manager.py, 73, INFO, Processing ticker NVDA\n",
+      "2024-10-23 21:20:04,374, data_manager.py, 108, INFO, Getting stock price data for NVDA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:04,374, data_manager.py, 108, INFO, Getting stock price data for NVDA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:04,593, data_manager.py, 82, INFO, Saving data for NVDA by year\n",
+      "2024-10-23 21:20:04,593, data_manager.py, 82, INFO, Saving data for NVDA by year\n",
+      "2024-10-23 21:20:05,478, data_manager.py, 73, INFO, Processing ticker NVR\n",
+      "2024-10-23 21:20:05,478, data_manager.py, 73, INFO, Processing ticker NVR\n",
+      "2024-10-23 21:20:05,480, data_manager.py, 108, INFO, Getting stock price data for NVR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:05,480, data_manager.py, 108, INFO, Getting stock price data for NVR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:05,637, data_manager.py, 82, INFO, Saving data for NVR by year\n",
+      "2024-10-23 21:20:05,637, data_manager.py, 82, INFO, Saving data for NVR by year\n",
+      "2024-10-23 21:20:06,545, data_manager.py, 73, INFO, Processing ticker NXPI\n",
+      "2024-10-23 21:20:06,545, data_manager.py, 73, INFO, Processing ticker NXPI\n",
+      "2024-10-23 21:20:06,546, data_manager.py, 108, INFO, Getting stock price data for NXPI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:06,546, data_manager.py, 108, INFO, Getting stock price data for NXPI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:06,700, data_manager.py, 82, INFO, Saving data for NXPI by year\n",
+      "2024-10-23 21:20:06,700, data_manager.py, 82, INFO, Saving data for NXPI by year\n",
+      "2024-10-23 21:20:07,393, data_manager.py, 73, INFO, Processing ticker ORLY\n",
+      "2024-10-23 21:20:07,393, data_manager.py, 73, INFO, Processing ticker ORLY\n",
+      "2024-10-23 21:20:07,396, data_manager.py, 108, INFO, Getting stock price data for ORLY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:07,396, data_manager.py, 108, INFO, Getting stock price data for ORLY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:07,553, data_manager.py, 82, INFO, Saving data for ORLY by year\n",
+      "2024-10-23 21:20:07,553, data_manager.py, 82, INFO, Saving data for ORLY by year\n",
+      "2024-10-23 21:20:08,626, data_manager.py, 73, INFO, Processing ticker OXY\n",
+      "2024-10-23 21:20:08,626, data_manager.py, 73, INFO, Processing ticker OXY\n",
+      "2024-10-23 21:20:08,628, data_manager.py, 108, INFO, Getting stock price data for OXY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:08,628, data_manager.py, 108, INFO, Getting stock price data for OXY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:08,885, data_manager.py, 82, INFO, Saving data for OXY by year\n",
+      "2024-10-23 21:20:08,885, data_manager.py, 82, INFO, Saving data for OXY by year\n",
+      "2024-10-23 21:20:09,849, data_manager.py, 73, INFO, Processing ticker ODFL\n",
+      "2024-10-23 21:20:09,849, data_manager.py, 73, INFO, Processing ticker ODFL\n",
+      "2024-10-23 21:20:09,850, data_manager.py, 108, INFO, Getting stock price data for ODFL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:09,850, data_manager.py, 108, INFO, Getting stock price data for ODFL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:10,047, data_manager.py, 82, INFO, Saving data for ODFL by year\n",
+      "2024-10-23 21:20:10,047, data_manager.py, 82, INFO, Saving data for ODFL by year\n",
+      "2024-10-23 21:20:11,201, data_manager.py, 73, INFO, Processing ticker OMC\n",
+      "2024-10-23 21:20:11,201, data_manager.py, 73, INFO, Processing ticker OMC\n",
+      "2024-10-23 21:20:11,202, data_manager.py, 108, INFO, Getting stock price data for OMC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:11,202, data_manager.py, 108, INFO, Getting stock price data for OMC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:11,455, data_manager.py, 82, INFO, Saving data for OMC by year\n",
+      "2024-10-23 21:20:11,455, data_manager.py, 82, INFO, Saving data for OMC by year\n",
+      "2024-10-23 21:20:12,541, data_manager.py, 73, INFO, Processing ticker ON\n",
+      "2024-10-23 21:20:12,541, data_manager.py, 73, INFO, Processing ticker ON\n",
+      "2024-10-23 21:20:12,542, data_manager.py, 108, INFO, Getting stock price data for ON from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:12,542, data_manager.py, 108, INFO, Getting stock price data for ON from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:12,706, data_manager.py, 82, INFO, Saving data for ON by year\n",
+      "2024-10-23 21:20:12,706, data_manager.py, 82, INFO, Saving data for ON by year\n",
+      "2024-10-23 21:20:13,622, data_manager.py, 73, INFO, Processing ticker OKE\n",
+      "2024-10-23 21:20:13,622, data_manager.py, 73, INFO, Processing ticker OKE\n",
+      "2024-10-23 21:20:13,624, data_manager.py, 108, INFO, Getting stock price data for OKE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:13,624, data_manager.py, 108, INFO, Getting stock price data for OKE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:13,888, data_manager.py, 82, INFO, Saving data for OKE by year\n",
+      "2024-10-23 21:20:13,888, data_manager.py, 82, INFO, Saving data for OKE by year\n",
+      "2024-10-23 21:20:14,803, data_manager.py, 73, INFO, Processing ticker ORCL\n",
+      "2024-10-23 21:20:14,803, data_manager.py, 73, INFO, Processing ticker ORCL\n",
+      "2024-10-23 21:20:14,804, data_manager.py, 108, INFO, Getting stock price data for ORCL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:14,804, data_manager.py, 108, INFO, Getting stock price data for ORCL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:15,037, data_manager.py, 82, INFO, Saving data for ORCL by year\n",
+      "2024-10-23 21:20:15,037, data_manager.py, 82, INFO, Saving data for ORCL by year\n",
+      "2024-10-23 21:20:15,919, data_manager.py, 73, INFO, Processing ticker OTIS\n",
+      "2024-10-23 21:20:15,919, data_manager.py, 73, INFO, Processing ticker OTIS\n",
+      "2024-10-23 21:20:15,921, data_manager.py, 108, INFO, Getting stock price data for OTIS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:15,921, data_manager.py, 108, INFO, Getting stock price data for OTIS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:16,031, data_manager.py, 82, INFO, Saving data for OTIS by year\n",
+      "2024-10-23 21:20:16,031, data_manager.py, 82, INFO, Saving data for OTIS by year\n",
+      "2024-10-23 21:20:16,245, data_manager.py, 73, INFO, Processing ticker PCAR\n",
+      "2024-10-23 21:20:16,245, data_manager.py, 73, INFO, Processing ticker PCAR\n",
+      "2024-10-23 21:20:16,247, data_manager.py, 108, INFO, Getting stock price data for PCAR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:16,247, data_manager.py, 108, INFO, Getting stock price data for PCAR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:16,485, data_manager.py, 82, INFO, Saving data for PCAR by year\n",
+      "2024-10-23 21:20:16,485, data_manager.py, 82, INFO, Saving data for PCAR by year\n",
+      "2024-10-23 21:20:17,606, data_manager.py, 73, INFO, Processing ticker PKG\n",
+      "2024-10-23 21:20:17,606, data_manager.py, 73, INFO, Processing ticker PKG\n",
+      "2024-10-23 21:20:17,608, data_manager.py, 108, INFO, Getting stock price data for PKG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:17,608, data_manager.py, 108, INFO, Getting stock price data for PKG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:17,831, data_manager.py, 82, INFO, Saving data for PKG by year\n",
+      "2024-10-23 21:20:17,831, data_manager.py, 82, INFO, Saving data for PKG by year\n",
+      "2024-10-23 21:20:18,848, data_manager.py, 73, INFO, Processing ticker PANW\n",
+      "2024-10-23 21:20:18,848, data_manager.py, 73, INFO, Processing ticker PANW\n",
+      "2024-10-23 21:20:18,849, data_manager.py, 108, INFO, Getting stock price data for PANW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:18,849, data_manager.py, 108, INFO, Getting stock price data for PANW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:18,993, data_manager.py, 82, INFO, Saving data for PANW by year\n",
+      "2024-10-23 21:20:18,993, data_manager.py, 82, INFO, Saving data for PANW by year\n",
+      "2024-10-23 21:20:19,500, data_manager.py, 73, INFO, Processing ticker PARA\n",
+      "2024-10-23 21:20:19,500, data_manager.py, 73, INFO, Processing ticker PARA\n",
+      "2024-10-23 21:20:19,502, data_manager.py, 108, INFO, Getting stock price data for PARA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:19,502, data_manager.py, 108, INFO, Getting stock price data for PARA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:19,767, data_manager.py, 82, INFO, Saving data for PARA by year\n",
+      "2024-10-23 21:20:19,767, data_manager.py, 82, INFO, Saving data for PARA by year\n",
+      "2024-10-23 21:20:20,605, data_manager.py, 73, INFO, Processing ticker PH\n",
+      "2024-10-23 21:20:20,605, data_manager.py, 73, INFO, Processing ticker PH\n",
+      "2024-10-23 21:20:20,607, data_manager.py, 108, INFO, Getting stock price data for PH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:20,607, data_manager.py, 108, INFO, Getting stock price data for PH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:20,857, data_manager.py, 82, INFO, Saving data for PH by year\n",
+      "2024-10-23 21:20:20,857, data_manager.py, 82, INFO, Saving data for PH by year\n",
+      "2024-10-23 21:20:21,950, data_manager.py, 73, INFO, Processing ticker PAYX\n",
+      "2024-10-23 21:20:21,950, data_manager.py, 73, INFO, Processing ticker PAYX\n",
+      "2024-10-23 21:20:21,952, data_manager.py, 108, INFO, Getting stock price data for PAYX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:21,952, data_manager.py, 108, INFO, Getting stock price data for PAYX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:22,190, data_manager.py, 82, INFO, Saving data for PAYX by year\n",
+      "2024-10-23 21:20:22,190, data_manager.py, 82, INFO, Saving data for PAYX by year\n",
+      "2024-10-23 21:20:23,232, data_manager.py, 73, INFO, Processing ticker PAYC\n",
+      "2024-10-23 21:20:23,232, data_manager.py, 73, INFO, Processing ticker PAYC\n",
+      "2024-10-23 21:20:23,233, data_manager.py, 108, INFO, Getting stock price data for PAYC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:23,233, data_manager.py, 108, INFO, Getting stock price data for PAYC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:23,354, data_manager.py, 82, INFO, Saving data for PAYC by year\n",
+      "2024-10-23 21:20:23,354, data_manager.py, 82, INFO, Saving data for PAYC by year\n",
+      "2024-10-23 21:20:23,862, data_manager.py, 73, INFO, Processing ticker PYPL\n",
+      "2024-10-23 21:20:23,862, data_manager.py, 73, INFO, Processing ticker PYPL\n",
+      "2024-10-23 21:20:23,864, data_manager.py, 108, INFO, Getting stock price data for PYPL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:23,864, data_manager.py, 108, INFO, Getting stock price data for PYPL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:23,994, data_manager.py, 82, INFO, Saving data for PYPL by year\n",
+      "2024-10-23 21:20:23,994, data_manager.py, 82, INFO, Saving data for PYPL by year\n",
+      "2024-10-23 21:20:24,443, data_manager.py, 73, INFO, Processing ticker PNR\n",
+      "2024-10-23 21:20:24,443, data_manager.py, 73, INFO, Processing ticker PNR\n",
+      "2024-10-23 21:20:24,445, data_manager.py, 108, INFO, Getting stock price data for PNR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:24,445, data_manager.py, 108, INFO, Getting stock price data for PNR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:24,745, data_manager.py, 82, INFO, Saving data for PNR by year\n",
+      "2024-10-23 21:20:24,745, data_manager.py, 82, INFO, Saving data for PNR by year\n",
+      "2024-10-23 21:20:25,899, data_manager.py, 73, INFO, Processing ticker PEP\n",
+      "2024-10-23 21:20:25,899, data_manager.py, 73, INFO, Processing ticker PEP\n",
+      "2024-10-23 21:20:25,900, data_manager.py, 108, INFO, Getting stock price data for PEP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:25,900, data_manager.py, 108, INFO, Getting stock price data for PEP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:26,155, data_manager.py, 82, INFO, Saving data for PEP by year\n",
+      "2024-10-23 21:20:26,155, data_manager.py, 82, INFO, Saving data for PEP by year\n",
+      "2024-10-23 21:20:27,221, data_manager.py, 73, INFO, Processing ticker PFE\n",
+      "2024-10-23 21:20:27,221, data_manager.py, 73, INFO, Processing ticker PFE\n",
+      "2024-10-23 21:20:27,223, data_manager.py, 108, INFO, Getting stock price data for PFE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:27,223, data_manager.py, 108, INFO, Getting stock price data for PFE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:27,495, data_manager.py, 82, INFO, Saving data for PFE by year\n",
+      "2024-10-23 21:20:27,495, data_manager.py, 82, INFO, Saving data for PFE by year\n",
+      "2024-10-23 21:20:28,397, data_manager.py, 73, INFO, Processing ticker PCG\n",
+      "2024-10-23 21:20:28,397, data_manager.py, 73, INFO, Processing ticker PCG\n",
+      "2024-10-23 21:20:28,398, data_manager.py, 108, INFO, Getting stock price data for PCG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:28,398, data_manager.py, 108, INFO, Getting stock price data for PCG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:28,657, data_manager.py, 82, INFO, Saving data for PCG by year\n",
+      "2024-10-23 21:20:28,657, data_manager.py, 82, INFO, Saving data for PCG by year\n",
+      "2024-10-23 21:20:29,522, data_manager.py, 73, INFO, Processing ticker PM\n",
+      "2024-10-23 21:20:29,522, data_manager.py, 73, INFO, Processing ticker PM\n",
+      "2024-10-23 21:20:29,523, data_manager.py, 108, INFO, Getting stock price data for PM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:29,523, data_manager.py, 108, INFO, Getting stock price data for PM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:29,701, data_manager.py, 82, INFO, Saving data for PM by year\n",
+      "2024-10-23 21:20:29,701, data_manager.py, 82, INFO, Saving data for PM by year\n",
+      "2024-10-23 21:20:30,448, data_manager.py, 73, INFO, Processing ticker PSX\n",
+      "2024-10-23 21:20:30,448, data_manager.py, 73, INFO, Processing ticker PSX\n",
+      "2024-10-23 21:20:30,449, data_manager.py, 108, INFO, Getting stock price data for PSX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:30,449, data_manager.py, 108, INFO, Getting stock price data for PSX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:30,617, data_manager.py, 82, INFO, Saving data for PSX by year\n",
+      "2024-10-23 21:20:30,617, data_manager.py, 82, INFO, Saving data for PSX by year\n",
+      "2024-10-23 21:20:31,139, data_manager.py, 73, INFO, Processing ticker PNW\n",
+      "2024-10-23 21:20:31,139, data_manager.py, 73, INFO, Processing ticker PNW\n",
+      "2024-10-23 21:20:31,141, data_manager.py, 108, INFO, Getting stock price data for PNW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:31,141, data_manager.py, 108, INFO, Getting stock price data for PNW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:31,376, data_manager.py, 82, INFO, Saving data for PNW by year\n",
+      "2024-10-23 21:20:31,376, data_manager.py, 82, INFO, Saving data for PNW by year\n",
+      "2024-10-23 21:20:32,524, data_manager.py, 73, INFO, Processing ticker PXD\n",
+      "2024-10-23 21:20:32,524, data_manager.py, 73, INFO, Processing ticker PXD\n",
+      "2024-10-23 21:20:32,526, data_manager.py, 108, INFO, Getting stock price data for PXD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:32,526, data_manager.py, 108, INFO, Getting stock price data for PXD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['PXD']: YFTzMissingError('$%ticker%: possibly delisted; No timezone found')\n",
+      "2024-10-23 21:20:33,914, data_manager.py, 82, INFO, Saving data for PXD by year\n",
+      "2024-10-23 21:20:33,914, data_manager.py, 82, INFO, Saving data for PXD by year\n",
+      "2024-10-23 21:20:33,916, data_manager.py, 100, WARNING, No data found for PXD\n",
+      "2024-10-23 21:20:33,916, data_manager.py, 100, WARNING, No data found for PXD\n",
+      "2024-10-23 21:20:33,918, data_manager.py, 73, INFO, Processing ticker PNC\n",
+      "2024-10-23 21:20:33,918, data_manager.py, 73, INFO, Processing ticker PNC\n",
+      "2024-10-23 21:20:33,920, data_manager.py, 108, INFO, Getting stock price data for PNC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:33,920, data_manager.py, 108, INFO, Getting stock price data for PNC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:34,196, data_manager.py, 82, INFO, Saving data for PNC by year\n",
+      "2024-10-23 21:20:34,196, data_manager.py, 82, INFO, Saving data for PNC by year\n",
+      "2024-10-23 21:20:35,114, data_manager.py, 73, INFO, Processing ticker POOL\n",
+      "2024-10-23 21:20:35,114, data_manager.py, 73, INFO, Processing ticker POOL\n",
+      "2024-10-23 21:20:35,115, data_manager.py, 108, INFO, Getting stock price data for POOL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:35,115, data_manager.py, 108, INFO, Getting stock price data for POOL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:35,313, data_manager.py, 82, INFO, Saving data for POOL by year\n",
+      "2024-10-23 21:20:35,313, data_manager.py, 82, INFO, Saving data for POOL by year\n",
+      "2024-10-23 21:20:36,391, data_manager.py, 73, INFO, Processing ticker PPG\n",
+      "2024-10-23 21:20:36,391, data_manager.py, 73, INFO, Processing ticker PPG\n",
+      "2024-10-23 21:20:36,392, data_manager.py, 108, INFO, Getting stock price data for PPG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:36,392, data_manager.py, 108, INFO, Getting stock price data for PPG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:36,652, data_manager.py, 82, INFO, Saving data for PPG by year\n",
+      "2024-10-23 21:20:36,652, data_manager.py, 82, INFO, Saving data for PPG by year\n",
+      "2024-10-23 21:20:38,143, data_manager.py, 73, INFO, Processing ticker PPL\n",
+      "2024-10-23 21:20:38,143, data_manager.py, 73, INFO, Processing ticker PPL\n",
+      "2024-10-23 21:20:38,144, data_manager.py, 108, INFO, Getting stock price data for PPL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:38,144, data_manager.py, 108, INFO, Getting stock price data for PPL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:38,466, data_manager.py, 82, INFO, Saving data for PPL by year\n",
+      "2024-10-23 21:20:38,466, data_manager.py, 82, INFO, Saving data for PPL by year\n",
+      "2024-10-23 21:20:39,623, data_manager.py, 73, INFO, Processing ticker PFG\n",
+      "2024-10-23 21:20:39,623, data_manager.py, 73, INFO, Processing ticker PFG\n",
+      "2024-10-23 21:20:39,624, data_manager.py, 108, INFO, Getting stock price data for PFG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:39,624, data_manager.py, 108, INFO, Getting stock price data for PFG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:39,885, data_manager.py, 82, INFO, Saving data for PFG by year\n",
+      "2024-10-23 21:20:39,885, data_manager.py, 82, INFO, Saving data for PFG by year\n",
+      "2024-10-23 21:20:40,806, data_manager.py, 73, INFO, Processing ticker PG\n",
+      "2024-10-23 21:20:40,806, data_manager.py, 73, INFO, Processing ticker PG\n",
+      "2024-10-23 21:20:40,808, data_manager.py, 108, INFO, Getting stock price data for PG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:40,808, data_manager.py, 108, INFO, Getting stock price data for PG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:41,118, data_manager.py, 82, INFO, Saving data for PG by year\n",
+      "2024-10-23 21:20:41,118, data_manager.py, 82, INFO, Saving data for PG by year\n",
+      "2024-10-23 21:20:42,491, data_manager.py, 73, INFO, Processing ticker PGR\n",
+      "2024-10-23 21:20:42,491, data_manager.py, 73, INFO, Processing ticker PGR\n",
+      "2024-10-23 21:20:42,493, data_manager.py, 108, INFO, Getting stock price data for PGR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:42,493, data_manager.py, 108, INFO, Getting stock price data for PGR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:42,802, data_manager.py, 82, INFO, Saving data for PGR by year\n",
+      "2024-10-23 21:20:42,802, data_manager.py, 82, INFO, Saving data for PGR by year\n",
+      "2024-10-23 21:20:44,038, data_manager.py, 73, INFO, Processing ticker PLD\n",
+      "2024-10-23 21:20:44,038, data_manager.py, 73, INFO, Processing ticker PLD\n",
+      "2024-10-23 21:20:44,040, data_manager.py, 108, INFO, Getting stock price data for PLD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:44,040, data_manager.py, 108, INFO, Getting stock price data for PLD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:44,248, data_manager.py, 82, INFO, Saving data for PLD by year\n",
+      "2024-10-23 21:20:44,248, data_manager.py, 82, INFO, Saving data for PLD by year\n",
+      "2024-10-23 21:20:45,619, data_manager.py, 73, INFO, Processing ticker PRU\n",
+      "2024-10-23 21:20:45,619, data_manager.py, 73, INFO, Processing ticker PRU\n",
+      "2024-10-23 21:20:45,621, data_manager.py, 108, INFO, Getting stock price data for PRU from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:45,621, data_manager.py, 108, INFO, Getting stock price data for PRU from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:06,474, data_manager.py, 82, INFO, Saving data for PRU by year\n",
+      "2024-10-23 21:21:06,474, data_manager.py, 82, INFO, Saving data for PRU by year\n",
+      "2024-10-23 21:20:46,650, data_manager.py, 73, INFO, Processing ticker PEG\n",
+      "2024-10-23 21:20:46,650, data_manager.py, 73, INFO, Processing ticker PEG\n",
+      "2024-10-23 21:20:46,651, data_manager.py, 108, INFO, Getting stock price data for PEG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:46,651, data_manager.py, 108, INFO, Getting stock price data for PEG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:46,906, data_manager.py, 82, INFO, Saving data for PEG by year\n",
+      "2024-10-23 21:20:46,906, data_manager.py, 82, INFO, Saving data for PEG by year\n",
+      "2024-10-23 21:20:48,086, data_manager.py, 73, INFO, Processing ticker PTC\n",
+      "2024-10-23 21:20:48,086, data_manager.py, 73, INFO, Processing ticker PTC\n",
+      "2024-10-23 21:20:48,088, data_manager.py, 108, INFO, Getting stock price data for PTC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:48,088, data_manager.py, 108, INFO, Getting stock price data for PTC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:48,284, data_manager.py, 82, INFO, Saving data for PTC by year\n",
+      "2024-10-23 21:20:48,284, data_manager.py, 82, INFO, Saving data for PTC by year\n",
+      "2024-10-23 21:20:49,695, data_manager.py, 73, INFO, Processing ticker PSA\n",
+      "2024-10-23 21:20:49,695, data_manager.py, 73, INFO, Processing ticker PSA\n",
+      "2024-10-23 21:20:49,697, data_manager.py, 108, INFO, Getting stock price data for PSA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:49,697, data_manager.py, 108, INFO, Getting stock price data for PSA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:49,939, data_manager.py, 82, INFO, Saving data for PSA by year\n",
+      "2024-10-23 21:20:49,939, data_manager.py, 82, INFO, Saving data for PSA by year\n",
+      "2024-10-23 21:20:51,206, data_manager.py, 73, INFO, Processing ticker PHM\n",
+      "2024-10-23 21:20:51,206, data_manager.py, 73, INFO, Processing ticker PHM\n",
+      "2024-10-23 21:20:51,207, data_manager.py, 108, INFO, Getting stock price data for PHM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:51,207, data_manager.py, 108, INFO, Getting stock price data for PHM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:51,472, data_manager.py, 82, INFO, Saving data for PHM by year\n",
+      "2024-10-23 21:20:51,472, data_manager.py, 82, INFO, Saving data for PHM by year\n",
+      "2024-10-23 21:20:52,672, data_manager.py, 73, INFO, Processing ticker QRVO\n",
+      "2024-10-23 21:20:52,672, data_manager.py, 73, INFO, Processing ticker QRVO\n",
+      "2024-10-23 21:20:52,673, data_manager.py, 108, INFO, Getting stock price data for QRVO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:52,673, data_manager.py, 108, INFO, Getting stock price data for QRVO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:52,791, data_manager.py, 82, INFO, Saving data for QRVO by year\n",
+      "2024-10-23 21:20:52,791, data_manager.py, 82, INFO, Saving data for QRVO by year\n",
+      "2024-10-23 21:20:53,252, data_manager.py, 73, INFO, Processing ticker PWR\n",
+      "2024-10-23 21:20:53,252, data_manager.py, 73, INFO, Processing ticker PWR\n",
+      "2024-10-23 21:20:53,253, data_manager.py, 108, INFO, Getting stock price data for PWR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:53,253, data_manager.py, 108, INFO, Getting stock price data for PWR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:53,450, data_manager.py, 82, INFO, Saving data for PWR by year\n",
+      "2024-10-23 21:20:53,450, data_manager.py, 82, INFO, Saving data for PWR by year\n",
+      "2024-10-23 21:20:54,638, data_manager.py, 73, INFO, Processing ticker QCOM\n",
+      "2024-10-23 21:20:54,638, data_manager.py, 73, INFO, Processing ticker QCOM\n",
+      "2024-10-23 21:20:54,640, data_manager.py, 108, INFO, Getting stock price data for QCOM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:54,640, data_manager.py, 108, INFO, Getting stock price data for QCOM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:54,980, data_manager.py, 82, INFO, Saving data for QCOM by year\n",
+      "2024-10-23 21:20:54,980, data_manager.py, 82, INFO, Saving data for QCOM by year\n",
+      "2024-10-23 21:20:55,998, data_manager.py, 73, INFO, Processing ticker DGX\n",
+      "2024-10-23 21:20:55,998, data_manager.py, 73, INFO, Processing ticker DGX\n",
+      "2024-10-23 21:20:56,000, data_manager.py, 108, INFO, Getting stock price data for DGX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:56,000, data_manager.py, 108, INFO, Getting stock price data for DGX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:56,215, data_manager.py, 82, INFO, Saving data for DGX by year\n",
+      "2024-10-23 21:20:56,215, data_manager.py, 82, INFO, Saving data for DGX by year\n",
+      "2024-10-23 21:20:57,300, data_manager.py, 73, INFO, Processing ticker RL\n",
+      "2024-10-23 21:20:57,300, data_manager.py, 73, INFO, Processing ticker RL\n",
+      "2024-10-23 21:20:57,301, data_manager.py, 108, INFO, Getting stock price data for RL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:57,301, data_manager.py, 108, INFO, Getting stock price data for RL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:57,520, data_manager.py, 82, INFO, Saving data for RL by year\n",
+      "2024-10-23 21:20:57,520, data_manager.py, 82, INFO, Saving data for RL by year\n",
+      "2024-10-23 21:20:58,561, data_manager.py, 73, INFO, Processing ticker RJF\n",
+      "2024-10-23 21:20:58,561, data_manager.py, 73, INFO, Processing ticker RJF\n",
+      "2024-10-23 21:20:58,562, data_manager.py, 108, INFO, Getting stock price data for RJF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:58,562, data_manager.py, 108, INFO, Getting stock price data for RJF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:20:58,816, data_manager.py, 82, INFO, Saving data for RJF by year\n",
+      "2024-10-23 21:20:58,816, data_manager.py, 82, INFO, Saving data for RJF by year\n",
+      "2024-10-23 21:20:59,801, data_manager.py, 73, INFO, Processing ticker RTX\n",
+      "2024-10-23 21:20:59,801, data_manager.py, 73, INFO, Processing ticker RTX\n",
+      "2024-10-23 21:20:59,803, data_manager.py, 108, INFO, Getting stock price data for RTX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:20:59,803, data_manager.py, 108, INFO, Getting stock price data for RTX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:00,244, data_manager.py, 82, INFO, Saving data for RTX by year\n",
+      "2024-10-23 21:21:00,244, data_manager.py, 82, INFO, Saving data for RTX by year\n",
+      "2024-10-23 21:21:01,239, data_manager.py, 73, INFO, Processing ticker O\n",
+      "2024-10-23 21:21:01,239, data_manager.py, 73, INFO, Processing ticker O\n",
+      "2024-10-23 21:21:01,240, data_manager.py, 108, INFO, Getting stock price data for O from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:01,240, data_manager.py, 108, INFO, Getting stock price data for O from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:01,512, data_manager.py, 82, INFO, Saving data for O by year\n",
+      "2024-10-23 21:21:01,512, data_manager.py, 82, INFO, Saving data for O by year\n",
+      "2024-10-23 21:21:02,566, data_manager.py, 73, INFO, Processing ticker REG\n",
+      "2024-10-23 21:21:02,566, data_manager.py, 73, INFO, Processing ticker REG\n",
+      "2024-10-23 21:21:02,567, data_manager.py, 108, INFO, Getting stock price data for REG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:02,567, data_manager.py, 108, INFO, Getting stock price data for REG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:02,788, data_manager.py, 82, INFO, Saving data for REG by year\n",
+      "2024-10-23 21:21:02,788, data_manager.py, 82, INFO, Saving data for REG by year\n",
+      "2024-10-23 21:21:03,804, data_manager.py, 73, INFO, Processing ticker REGN\n",
+      "2024-10-23 21:21:03,804, data_manager.py, 73, INFO, Processing ticker REGN\n",
+      "2024-10-23 21:21:03,805, data_manager.py, 108, INFO, Getting stock price data for REGN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:03,805, data_manager.py, 108, INFO, Getting stock price data for REGN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:03,959, data_manager.py, 82, INFO, Saving data for REGN by year\n",
+      "2024-10-23 21:21:03,959, data_manager.py, 82, INFO, Saving data for REGN by year\n",
+      "2024-10-23 21:21:04,952, data_manager.py, 73, INFO, Processing ticker RF\n",
+      "2024-10-23 21:21:04,952, data_manager.py, 73, INFO, Processing ticker RF\n",
+      "2024-10-23 21:21:04,953, data_manager.py, 108, INFO, Getting stock price data for RF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:04,953, data_manager.py, 108, INFO, Getting stock price data for RF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:05,305, data_manager.py, 82, INFO, Saving data for RF by year\n",
+      "2024-10-23 21:21:05,305, data_manager.py, 82, INFO, Saving data for RF by year\n",
+      "2024-10-23 21:21:06,396, data_manager.py, 73, INFO, Processing ticker RSG\n",
+      "2024-10-23 21:21:06,396, data_manager.py, 73, INFO, Processing ticker RSG\n",
+      "2024-10-23 21:21:06,398, data_manager.py, 108, INFO, Getting stock price data for RSG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:06,398, data_manager.py, 108, INFO, Getting stock price data for RSG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:06,618, data_manager.py, 82, INFO, Saving data for RSG by year\n",
+      "2024-10-23 21:21:06,618, data_manager.py, 82, INFO, Saving data for RSG by year\n",
+      "2024-10-23 21:21:07,490, data_manager.py, 73, INFO, Processing ticker RMD\n",
+      "2024-10-23 21:21:07,490, data_manager.py, 73, INFO, Processing ticker RMD\n",
+      "2024-10-23 21:21:07,491, data_manager.py, 108, INFO, Getting stock price data for RMD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:07,491, data_manager.py, 108, INFO, Getting stock price data for RMD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:07,697, data_manager.py, 82, INFO, Saving data for RMD by year\n",
+      "2024-10-23 21:21:07,697, data_manager.py, 82, INFO, Saving data for RMD by year\n",
+      "2024-10-23 21:21:08,625, data_manager.py, 73, INFO, Processing ticker RVTY\n",
+      "2024-10-23 21:21:08,625, data_manager.py, 73, INFO, Processing ticker RVTY\n",
+      "2024-10-23 21:21:08,626, data_manager.py, 108, INFO, Getting stock price data for RVTY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:08,626, data_manager.py, 108, INFO, Getting stock price data for RVTY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:08,942, data_manager.py, 82, INFO, Saving data for RVTY by year\n",
+      "2024-10-23 21:21:08,942, data_manager.py, 82, INFO, Saving data for RVTY by year\n",
+      "2024-10-23 21:21:09,981, data_manager.py, 73, INFO, Processing ticker RHI\n",
+      "2024-10-23 21:21:09,981, data_manager.py, 73, INFO, Processing ticker RHI\n",
+      "2024-10-23 21:21:09,983, data_manager.py, 108, INFO, Getting stock price data for RHI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:09,983, data_manager.py, 108, INFO, Getting stock price data for RHI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:10,196, data_manager.py, 82, INFO, Saving data for RHI by year\n",
+      "2024-10-23 21:21:10,196, data_manager.py, 82, INFO, Saving data for RHI by year\n",
+      "2024-10-23 21:21:11,239, data_manager.py, 73, INFO, Processing ticker ROK\n",
+      "2024-10-23 21:21:11,239, data_manager.py, 73, INFO, Processing ticker ROK\n",
+      "2024-10-23 21:21:11,240, data_manager.py, 108, INFO, Getting stock price data for ROK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:11,240, data_manager.py, 108, INFO, Getting stock price data for ROK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:11,530, data_manager.py, 82, INFO, Saving data for ROK by year\n",
+      "2024-10-23 21:21:11,530, data_manager.py, 82, INFO, Saving data for ROK by year\n",
+      "2024-10-23 21:21:12,462, data_manager.py, 73, INFO, Processing ticker ROL\n",
+      "2024-10-23 21:21:12,462, data_manager.py, 73, INFO, Processing ticker ROL\n",
+      "2024-10-23 21:21:12,464, data_manager.py, 108, INFO, Getting stock price data for ROL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:12,464, data_manager.py, 108, INFO, Getting stock price data for ROL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:12,706, data_manager.py, 82, INFO, Saving data for ROL by year\n",
+      "2024-10-23 21:21:12,706, data_manager.py, 82, INFO, Saving data for ROL by year\n",
+      "2024-10-23 21:21:13,980, data_manager.py, 73, INFO, Processing ticker ROP\n",
+      "2024-10-23 21:21:13,980, data_manager.py, 73, INFO, Processing ticker ROP\n",
+      "2024-10-23 21:21:13,981, data_manager.py, 108, INFO, Getting stock price data for ROP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:13,981, data_manager.py, 108, INFO, Getting stock price data for ROP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:14,230, data_manager.py, 82, INFO, Saving data for ROP by year\n",
+      "2024-10-23 21:21:14,230, data_manager.py, 82, INFO, Saving data for ROP by year\n",
+      "2024-10-23 21:21:15,546, data_manager.py, 73, INFO, Processing ticker ROST\n",
+      "2024-10-23 21:21:15,546, data_manager.py, 73, INFO, Processing ticker ROST\n",
+      "2024-10-23 21:21:15,548, data_manager.py, 108, INFO, Getting stock price data for ROST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:15,548, data_manager.py, 108, INFO, Getting stock price data for ROST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:15,791, data_manager.py, 82, INFO, Saving data for ROST by year\n",
+      "2024-10-23 21:21:15,791, data_manager.py, 82, INFO, Saving data for ROST by year\n",
+      "2024-10-23 21:21:16,884, data_manager.py, 73, INFO, Processing ticker RCL\n",
+      "2024-10-23 21:21:16,884, data_manager.py, 73, INFO, Processing ticker RCL\n",
+      "2024-10-23 21:21:16,885, data_manager.py, 108, INFO, Getting stock price data for RCL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:16,885, data_manager.py, 108, INFO, Getting stock price data for RCL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:17,094, data_manager.py, 82, INFO, Saving data for RCL by year\n",
+      "2024-10-23 21:21:17,094, data_manager.py, 82, INFO, Saving data for RCL by year\n",
+      "2024-10-23 21:21:18,070, data_manager.py, 73, INFO, Processing ticker SPGI\n",
+      "2024-10-23 21:21:18,070, data_manager.py, 73, INFO, Processing ticker SPGI\n",
+      "2024-10-23 21:21:18,071, data_manager.py, 108, INFO, Getting stock price data for SPGI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:18,071, data_manager.py, 108, INFO, Getting stock price data for SPGI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:18,384, data_manager.py, 82, INFO, Saving data for SPGI by year\n",
+      "2024-10-23 21:21:18,384, data_manager.py, 82, INFO, Saving data for SPGI by year\n",
+      "2024-10-23 21:21:19,553, data_manager.py, 73, INFO, Processing ticker CRM\n",
+      "2024-10-23 21:21:19,553, data_manager.py, 73, INFO, Processing ticker CRM\n",
+      "2024-10-23 21:21:19,554, data_manager.py, 108, INFO, Getting stock price data for CRM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:19,554, data_manager.py, 108, INFO, Getting stock price data for CRM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:19,755, data_manager.py, 82, INFO, Saving data for CRM by year\n",
+      "2024-10-23 21:21:19,755, data_manager.py, 82, INFO, Saving data for CRM by year\n",
+      "2024-10-23 21:21:20,618, data_manager.py, 73, INFO, Processing ticker SBAC\n",
+      "2024-10-23 21:21:20,618, data_manager.py, 73, INFO, Processing ticker SBAC\n",
+      "2024-10-23 21:21:20,620, data_manager.py, 108, INFO, Getting stock price data for SBAC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:20,620, data_manager.py, 108, INFO, Getting stock price data for SBAC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:20,813, data_manager.py, 82, INFO, Saving data for SBAC by year\n",
+      "2024-10-23 21:21:20,813, data_manager.py, 82, INFO, Saving data for SBAC by year\n",
+      "2024-10-23 21:21:21,779, data_manager.py, 73, INFO, Processing ticker SLB\n",
+      "2024-10-23 21:21:21,779, data_manager.py, 73, INFO, Processing ticker SLB\n",
+      "2024-10-23 21:21:21,781, data_manager.py, 108, INFO, Getting stock price data for SLB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:21,781, data_manager.py, 108, INFO, Getting stock price data for SLB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:22,049, data_manager.py, 82, INFO, Saving data for SLB by year\n",
+      "2024-10-23 21:21:22,049, data_manager.py, 82, INFO, Saving data for SLB by year\n",
+      "2024-10-23 21:21:22,960, data_manager.py, 73, INFO, Processing ticker STX\n",
+      "2024-10-23 21:21:22,960, data_manager.py, 73, INFO, Processing ticker STX\n",
+      "2024-10-23 21:21:22,962, data_manager.py, 108, INFO, Getting stock price data for STX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:22,962, data_manager.py, 108, INFO, Getting stock price data for STX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:23,150, data_manager.py, 82, INFO, Saving data for STX by year\n",
+      "2024-10-23 21:21:23,150, data_manager.py, 82, INFO, Saving data for STX by year\n",
+      "2024-10-23 21:21:24,174, data_manager.py, 73, INFO, Processing ticker SRE\n",
+      "2024-10-23 21:21:24,174, data_manager.py, 73, INFO, Processing ticker SRE\n",
+      "2024-10-23 21:21:24,175, data_manager.py, 108, INFO, Getting stock price data for SRE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:24,175, data_manager.py, 108, INFO, Getting stock price data for SRE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:24,439, data_manager.py, 82, INFO, Saving data for SRE by year\n",
+      "2024-10-23 21:21:24,439, data_manager.py, 82, INFO, Saving data for SRE by year\n",
+      "2024-10-23 21:21:46,530, data_manager.py, 73, INFO, Processing ticker NOW\n",
+      "2024-10-23 21:21:46,530, data_manager.py, 73, INFO, Processing ticker NOW\n",
+      "2024-10-23 21:21:46,531, data_manager.py, 108, INFO, Getting stock price data for NOW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:46,531, data_manager.py, 108, INFO, Getting stock price data for NOW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:25,664, data_manager.py, 82, INFO, Saving data for NOW by year\n",
+      "2024-10-23 21:21:25,664, data_manager.py, 82, INFO, Saving data for NOW by year\n",
+      "2024-10-23 21:21:26,302, data_manager.py, 73, INFO, Processing ticker SHW\n",
+      "2024-10-23 21:21:26,302, data_manager.py, 73, INFO, Processing ticker SHW\n",
+      "2024-10-23 21:21:26,303, data_manager.py, 108, INFO, Getting stock price data for SHW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:26,303, data_manager.py, 108, INFO, Getting stock price data for SHW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:26,541, data_manager.py, 82, INFO, Saving data for SHW by year\n",
+      "2024-10-23 21:21:26,541, data_manager.py, 82, INFO, Saving data for SHW by year\n",
+      "2024-10-23 21:21:27,554, data_manager.py, 73, INFO, Processing ticker SPG\n",
+      "2024-10-23 21:21:27,554, data_manager.py, 73, INFO, Processing ticker SPG\n",
+      "2024-10-23 21:21:27,555, data_manager.py, 108, INFO, Getting stock price data for SPG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:27,555, data_manager.py, 108, INFO, Getting stock price data for SPG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:27,819, data_manager.py, 82, INFO, Saving data for SPG by year\n",
+      "2024-10-23 21:21:27,819, data_manager.py, 82, INFO, Saving data for SPG by year\n",
+      "2024-10-23 21:21:29,041, data_manager.py, 73, INFO, Processing ticker SWKS\n",
+      "2024-10-23 21:21:29,041, data_manager.py, 73, INFO, Processing ticker SWKS\n",
+      "2024-10-23 21:21:29,043, data_manager.py, 108, INFO, Getting stock price data for SWKS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:29,043, data_manager.py, 108, INFO, Getting stock price data for SWKS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:29,272, data_manager.py, 82, INFO, Saving data for SWKS by year\n",
+      "2024-10-23 21:21:29,272, data_manager.py, 82, INFO, Saving data for SWKS by year\n",
+      "2024-10-23 21:21:30,118, data_manager.py, 73, INFO, Processing ticker SJM\n",
+      "2024-10-23 21:21:30,118, data_manager.py, 73, INFO, Processing ticker SJM\n",
+      "2024-10-23 21:21:30,120, data_manager.py, 108, INFO, Getting stock price data for SJM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:30,120, data_manager.py, 108, INFO, Getting stock price data for SJM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:30,318, data_manager.py, 82, INFO, Saving data for SJM by year\n",
+      "2024-10-23 21:21:30,318, data_manager.py, 82, INFO, Saving data for SJM by year\n",
+      "2024-10-23 21:21:31,318, data_manager.py, 73, INFO, Processing ticker SNA\n",
+      "2024-10-23 21:21:31,318, data_manager.py, 73, INFO, Processing ticker SNA\n",
+      "2024-10-23 21:21:31,319, data_manager.py, 108, INFO, Getting stock price data for SNA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:31,319, data_manager.py, 108, INFO, Getting stock price data for SNA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:31,548, data_manager.py, 82, INFO, Saving data for SNA by year\n",
+      "2024-10-23 21:21:31,548, data_manager.py, 82, INFO, Saving data for SNA by year\n",
+      "2024-10-23 21:21:32,528, data_manager.py, 73, INFO, Processing ticker SO\n",
+      "2024-10-23 21:21:32,528, data_manager.py, 73, INFO, Processing ticker SO\n",
+      "2024-10-23 21:21:32,529, data_manager.py, 108, INFO, Getting stock price data for SO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:32,529, data_manager.py, 108, INFO, Getting stock price data for SO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:33,000, data_manager.py, 82, INFO, Saving data for SO by year\n",
+      "2024-10-23 21:21:33,000, data_manager.py, 82, INFO, Saving data for SO by year\n",
+      "2024-10-23 21:21:34,053, data_manager.py, 73, INFO, Processing ticker LUV\n",
+      "2024-10-23 21:21:34,053, data_manager.py, 73, INFO, Processing ticker LUV\n",
+      "2024-10-23 21:21:34,054, data_manager.py, 108, INFO, Getting stock price data for LUV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:34,054, data_manager.py, 108, INFO, Getting stock price data for LUV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:34,311, data_manager.py, 82, INFO, Saving data for LUV by year\n",
+      "2024-10-23 21:21:34,311, data_manager.py, 82, INFO, Saving data for LUV by year\n",
+      "2024-10-23 21:21:35,236, data_manager.py, 73, INFO, Processing ticker SWK\n",
+      "2024-10-23 21:21:35,236, data_manager.py, 73, INFO, Processing ticker SWK\n",
+      "2024-10-23 21:21:35,238, data_manager.py, 108, INFO, Getting stock price data for SWK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:35,238, data_manager.py, 108, INFO, Getting stock price data for SWK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:35,474, data_manager.py, 82, INFO, Saving data for SWK by year\n",
+      "2024-10-23 21:21:35,474, data_manager.py, 82, INFO, Saving data for SWK by year\n",
+      "2024-10-23 21:21:36,407, data_manager.py, 73, INFO, Processing ticker SBUX\n",
+      "2024-10-23 21:21:36,407, data_manager.py, 73, INFO, Processing ticker SBUX\n",
+      "2024-10-23 21:21:36,409, data_manager.py, 108, INFO, Getting stock price data for SBUX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:36,409, data_manager.py, 108, INFO, Getting stock price data for SBUX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:36,620, data_manager.py, 82, INFO, Saving data for SBUX by year\n",
+      "2024-10-23 21:21:36,620, data_manager.py, 82, INFO, Saving data for SBUX by year\n",
+      "2024-10-23 21:21:37,687, data_manager.py, 73, INFO, Processing ticker STT\n",
+      "2024-10-23 21:21:37,687, data_manager.py, 73, INFO, Processing ticker STT\n",
+      "2024-10-23 21:21:37,689, data_manager.py, 108, INFO, Getting stock price data for STT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:37,689, data_manager.py, 108, INFO, Getting stock price data for STT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:37,920, data_manager.py, 82, INFO, Saving data for STT by year\n",
+      "2024-10-23 21:21:37,920, data_manager.py, 82, INFO, Saving data for STT by year\n",
+      "2024-10-23 21:21:39,278, data_manager.py, 73, INFO, Processing ticker STLD\n",
+      "2024-10-23 21:21:39,278, data_manager.py, 73, INFO, Processing ticker STLD\n",
+      "2024-10-23 21:21:39,279, data_manager.py, 108, INFO, Getting stock price data for STLD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:39,279, data_manager.py, 108, INFO, Getting stock price data for STLD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:39,489, data_manager.py, 82, INFO, Saving data for STLD by year\n",
+      "2024-10-23 21:21:39,489, data_manager.py, 82, INFO, Saving data for STLD by year\n",
+      "2024-10-23 21:21:40,499, data_manager.py, 73, INFO, Processing ticker STE\n",
+      "2024-10-23 21:21:40,499, data_manager.py, 73, INFO, Processing ticker STE\n",
+      "2024-10-23 21:21:40,501, data_manager.py, 108, INFO, Getting stock price data for STE from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:40,501, data_manager.py, 108, INFO, Getting stock price data for STE from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:40,698, data_manager.py, 82, INFO, Saving data for STE by year\n",
+      "2024-10-23 21:21:40,698, data_manager.py, 82, INFO, Saving data for STE by year\n",
+      "2024-10-23 21:21:41,711, data_manager.py, 73, INFO, Processing ticker SYK\n",
+      "2024-10-23 21:21:41,711, data_manager.py, 73, INFO, Processing ticker SYK\n",
+      "2024-10-23 21:21:41,712, data_manager.py, 108, INFO, Getting stock price data for SYK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:41,712, data_manager.py, 108, INFO, Getting stock price data for SYK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:41,928, data_manager.py, 82, INFO, Saving data for SYK by year\n",
+      "2024-10-23 21:21:41,928, data_manager.py, 82, INFO, Saving data for SYK by year\n",
+      "2024-10-23 21:21:43,233, data_manager.py, 73, INFO, Processing ticker SYF\n",
+      "2024-10-23 21:21:43,233, data_manager.py, 73, INFO, Processing ticker SYF\n",
+      "2024-10-23 21:21:43,234, data_manager.py, 108, INFO, Getting stock price data for SYF from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:43,234, data_manager.py, 108, INFO, Getting stock price data for SYF from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:43,481, data_manager.py, 82, INFO, Saving data for SYF by year\n",
+      "2024-10-23 21:21:43,481, data_manager.py, 82, INFO, Saving data for SYF by year\n",
+      "2024-10-23 21:21:43,885, data_manager.py, 73, INFO, Processing ticker SNPS\n",
+      "2024-10-23 21:21:43,885, data_manager.py, 73, INFO, Processing ticker SNPS\n",
+      "2024-10-23 21:21:43,887, data_manager.py, 108, INFO, Getting stock price data for SNPS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:43,887, data_manager.py, 108, INFO, Getting stock price data for SNPS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:44,081, data_manager.py, 82, INFO, Saving data for SNPS by year\n",
+      "2024-10-23 21:21:44,081, data_manager.py, 82, INFO, Saving data for SNPS by year\n",
+      "2024-10-23 21:21:45,057, data_manager.py, 73, INFO, Processing ticker SYY\n",
+      "2024-10-23 21:21:45,057, data_manager.py, 73, INFO, Processing ticker SYY\n",
+      "2024-10-23 21:21:45,059, data_manager.py, 108, INFO, Getting stock price data for SYY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:45,059, data_manager.py, 108, INFO, Getting stock price data for SYY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:45,317, data_manager.py, 82, INFO, Saving data for SYY by year\n",
+      "2024-10-23 21:21:45,317, data_manager.py, 82, INFO, Saving data for SYY by year\n",
+      "2024-10-23 21:21:46,418, data_manager.py, 73, INFO, Processing ticker TMUS\n",
+      "2024-10-23 21:21:46,418, data_manager.py, 73, INFO, Processing ticker TMUS\n",
+      "2024-10-23 21:21:46,419, data_manager.py, 108, INFO, Getting stock price data for TMUS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:46,419, data_manager.py, 108, INFO, Getting stock price data for TMUS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:46,590, data_manager.py, 82, INFO, Saving data for TMUS by year\n",
+      "2024-10-23 21:21:46,590, data_manager.py, 82, INFO, Saving data for TMUS by year\n",
+      "2024-10-23 21:21:47,402, data_manager.py, 73, INFO, Processing ticker TROW\n",
+      "2024-10-23 21:21:47,402, data_manager.py, 73, INFO, Processing ticker TROW\n",
+      "2024-10-23 21:21:47,403, data_manager.py, 108, INFO, Getting stock price data for TROW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:47,403, data_manager.py, 108, INFO, Getting stock price data for TROW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:47,682, data_manager.py, 82, INFO, Saving data for TROW by year\n",
+      "2024-10-23 21:21:47,682, data_manager.py, 82, INFO, Saving data for TROW by year\n",
+      "2024-10-23 21:21:48,710, data_manager.py, 73, INFO, Processing ticker TTWO\n",
+      "2024-10-23 21:21:48,710, data_manager.py, 73, INFO, Processing ticker TTWO\n",
+      "2024-10-23 21:21:48,711, data_manager.py, 108, INFO, Getting stock price data for TTWO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:48,711, data_manager.py, 108, INFO, Getting stock price data for TTWO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:49,020, data_manager.py, 82, INFO, Saving data for TTWO by year\n",
+      "2024-10-23 21:21:49,020, data_manager.py, 82, INFO, Saving data for TTWO by year\n",
+      "2024-10-23 21:21:50,074, data_manager.py, 73, INFO, Processing ticker TPR\n",
+      "2024-10-23 21:21:50,074, data_manager.py, 73, INFO, Processing ticker TPR\n",
+      "2024-10-23 21:21:50,075, data_manager.py, 108, INFO, Getting stock price data for TPR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:50,075, data_manager.py, 108, INFO, Getting stock price data for TPR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:50,266, data_manager.py, 82, INFO, Saving data for TPR by year\n",
+      "2024-10-23 21:21:50,266, data_manager.py, 82, INFO, Saving data for TPR by year\n",
+      "2024-10-23 21:21:51,217, data_manager.py, 73, INFO, Processing ticker TRGP\n",
+      "2024-10-23 21:21:51,217, data_manager.py, 73, INFO, Processing ticker TRGP\n",
+      "2024-10-23 21:21:51,218, data_manager.py, 108, INFO, Getting stock price data for TRGP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:51,218, data_manager.py, 108, INFO, Getting stock price data for TRGP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:51,416, data_manager.py, 82, INFO, Saving data for TRGP by year\n",
+      "2024-10-23 21:21:51,416, data_manager.py, 82, INFO, Saving data for TRGP by year\n",
+      "2024-10-23 21:21:52,034, data_manager.py, 73, INFO, Processing ticker TGT\n",
+      "2024-10-23 21:21:52,034, data_manager.py, 73, INFO, Processing ticker TGT\n",
+      "2024-10-23 21:21:52,035, data_manager.py, 108, INFO, Getting stock price data for TGT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:52,035, data_manager.py, 108, INFO, Getting stock price data for TGT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:52,283, data_manager.py, 82, INFO, Saving data for TGT by year\n",
+      "2024-10-23 21:21:52,283, data_manager.py, 82, INFO, Saving data for TGT by year\n",
+      "2024-10-23 21:21:53,506, data_manager.py, 73, INFO, Processing ticker TEL\n",
+      "2024-10-23 21:21:53,506, data_manager.py, 73, INFO, Processing ticker TEL\n",
+      "2024-10-23 21:21:53,508, data_manager.py, 108, INFO, Getting stock price data for TEL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:53,508, data_manager.py, 108, INFO, Getting stock price data for TEL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:53,695, data_manager.py, 82, INFO, Saving data for TEL by year\n",
+      "2024-10-23 21:21:53,695, data_manager.py, 82, INFO, Saving data for TEL by year\n",
+      "2024-10-23 21:21:54,623, data_manager.py, 73, INFO, Processing ticker TDY\n",
+      "2024-10-23 21:21:54,623, data_manager.py, 73, INFO, Processing ticker TDY\n",
+      "2024-10-23 21:21:54,625, data_manager.py, 108, INFO, Getting stock price data for TDY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:54,625, data_manager.py, 108, INFO, Getting stock price data for TDY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:54,791, data_manager.py, 82, INFO, Saving data for TDY by year\n",
+      "2024-10-23 21:21:54,791, data_manager.py, 82, INFO, Saving data for TDY by year\n",
+      "2024-10-23 21:21:55,939, data_manager.py, 73, INFO, Processing ticker TFX\n",
+      "2024-10-23 21:21:55,939, data_manager.py, 73, INFO, Processing ticker TFX\n",
+      "2024-10-23 21:21:55,941, data_manager.py, 108, INFO, Getting stock price data for TFX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:55,941, data_manager.py, 108, INFO, Getting stock price data for TFX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:56,161, data_manager.py, 82, INFO, Saving data for TFX by year\n",
+      "2024-10-23 21:21:56,161, data_manager.py, 82, INFO, Saving data for TFX by year\n",
+      "2024-10-23 21:21:57,114, data_manager.py, 73, INFO, Processing ticker TER\n",
+      "2024-10-23 21:21:57,114, data_manager.py, 73, INFO, Processing ticker TER\n",
+      "2024-10-23 21:21:57,116, data_manager.py, 108, INFO, Getting stock price data for TER from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:57,116, data_manager.py, 108, INFO, Getting stock price data for TER from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:57,300, data_manager.py, 82, INFO, Saving data for TER by year\n",
+      "2024-10-23 21:21:57,300, data_manager.py, 82, INFO, Saving data for TER by year\n",
+      "2024-10-23 21:21:58,382, data_manager.py, 73, INFO, Processing ticker TSLA\n",
+      "2024-10-23 21:21:58,382, data_manager.py, 73, INFO, Processing ticker TSLA\n",
+      "2024-10-23 21:21:58,383, data_manager.py, 108, INFO, Getting stock price data for TSLA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:58,383, data_manager.py, 108, INFO, Getting stock price data for TSLA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:58,562, data_manager.py, 82, INFO, Saving data for TSLA by year\n",
+      "2024-10-23 21:21:58,562, data_manager.py, 82, INFO, Saving data for TSLA by year\n",
+      "2024-10-23 21:21:59,080, data_manager.py, 73, INFO, Processing ticker TXN\n",
+      "2024-10-23 21:21:59,080, data_manager.py, 73, INFO, Processing ticker TXN\n",
+      "2024-10-23 21:21:59,081, data_manager.py, 108, INFO, Getting stock price data for TXN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:21:59,081, data_manager.py, 108, INFO, Getting stock price data for TXN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:21:59,349, data_manager.py, 82, INFO, Saving data for TXN by year\n",
+      "2024-10-23 21:21:59,349, data_manager.py, 82, INFO, Saving data for TXN by year\n",
+      "2024-10-23 21:22:00,447, data_manager.py, 73, INFO, Processing ticker TXT\n",
+      "2024-10-23 21:22:00,447, data_manager.py, 73, INFO, Processing ticker TXT\n",
+      "2024-10-23 21:22:00,449, data_manager.py, 108, INFO, Getting stock price data for TXT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:00,449, data_manager.py, 108, INFO, Getting stock price data for TXT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:00,709, data_manager.py, 82, INFO, Saving data for TXT by year\n",
+      "2024-10-23 21:22:00,709, data_manager.py, 82, INFO, Saving data for TXT by year\n",
+      "2024-10-23 21:22:01,555, data_manager.py, 73, INFO, Processing ticker TMO\n",
+      "2024-10-23 21:22:01,555, data_manager.py, 73, INFO, Processing ticker TMO\n",
+      "2024-10-23 21:22:01,556, data_manager.py, 108, INFO, Getting stock price data for TMO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:01,556, data_manager.py, 108, INFO, Getting stock price data for TMO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:01,800, data_manager.py, 82, INFO, Saving data for TMO by year\n",
+      "2024-10-23 21:22:01,800, data_manager.py, 82, INFO, Saving data for TMO by year\n",
+      "2024-10-23 21:22:02,735, data_manager.py, 73, INFO, Processing ticker TJX\n",
+      "2024-10-23 21:22:02,735, data_manager.py, 73, INFO, Processing ticker TJX\n",
+      "2024-10-23 21:22:02,736, data_manager.py, 108, INFO, Getting stock price data for TJX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:02,736, data_manager.py, 108, INFO, Getting stock price data for TJX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:02,971, data_manager.py, 82, INFO, Saving data for TJX by year\n",
+      "2024-10-23 21:22:02,971, data_manager.py, 82, INFO, Saving data for TJX by year\n",
+      "2024-10-23 21:22:04,298, data_manager.py, 73, INFO, Processing ticker TSCO\n",
+      "2024-10-23 21:22:04,298, data_manager.py, 73, INFO, Processing ticker TSCO\n",
+      "2024-10-23 21:22:04,299, data_manager.py, 108, INFO, Getting stock price data for TSCO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:04,299, data_manager.py, 108, INFO, Getting stock price data for TSCO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:04,514, data_manager.py, 82, INFO, Saving data for TSCO by year\n",
+      "2024-10-23 21:22:04,514, data_manager.py, 82, INFO, Saving data for TSCO by year\n",
+      "2024-10-23 21:22:05,796, data_manager.py, 73, INFO, Processing ticker TT\n",
+      "2024-10-23 21:22:05,796, data_manager.py, 73, INFO, Processing ticker TT\n",
+      "2024-10-23 21:22:05,797, data_manager.py, 108, INFO, Getting stock price data for TT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:05,797, data_manager.py, 108, INFO, Getting stock price data for TT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:06,143, data_manager.py, 82, INFO, Saving data for TT by year\n",
+      "2024-10-23 21:22:06,143, data_manager.py, 82, INFO, Saving data for TT by year\n",
+      "2024-10-23 21:22:07,100, data_manager.py, 73, INFO, Processing ticker TDG\n",
+      "2024-10-23 21:22:07,100, data_manager.py, 73, INFO, Processing ticker TDG\n",
+      "2024-10-23 21:22:07,101, data_manager.py, 108, INFO, Getting stock price data for TDG from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:07,101, data_manager.py, 108, INFO, Getting stock price data for TDG from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:07,360, data_manager.py, 82, INFO, Saving data for TDG by year\n",
+      "2024-10-23 21:22:07,360, data_manager.py, 82, INFO, Saving data for TDG by year\n",
+      "2024-10-23 21:22:08,133, data_manager.py, 73, INFO, Processing ticker TRV\n",
+      "2024-10-23 21:22:08,133, data_manager.py, 73, INFO, Processing ticker TRV\n",
+      "2024-10-23 21:22:08,134, data_manager.py, 108, INFO, Getting stock price data for TRV from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:08,134, data_manager.py, 108, INFO, Getting stock price data for TRV from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:08,477, data_manager.py, 82, INFO, Saving data for TRV by year\n",
+      "2024-10-23 21:22:08,477, data_manager.py, 82, INFO, Saving data for TRV by year\n",
+      "2024-10-23 21:22:09,495, data_manager.py, 73, INFO, Processing ticker TRMB\n",
+      "2024-10-23 21:22:09,495, data_manager.py, 73, INFO, Processing ticker TRMB\n",
+      "2024-10-23 21:22:09,496, data_manager.py, 108, INFO, Getting stock price data for TRMB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:09,496, data_manager.py, 108, INFO, Getting stock price data for TRMB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:09,800, data_manager.py, 82, INFO, Saving data for TRMB by year\n",
+      "2024-10-23 21:22:09,800, data_manager.py, 82, INFO, Saving data for TRMB by year\n",
+      "2024-10-23 21:22:10,710, data_manager.py, 73, INFO, Processing ticker TFC\n",
+      "2024-10-23 21:22:10,710, data_manager.py, 73, INFO, Processing ticker TFC\n",
+      "2024-10-23 21:22:10,711, data_manager.py, 108, INFO, Getting stock price data for TFC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:10,711, data_manager.py, 108, INFO, Getting stock price data for TFC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:11,144, data_manager.py, 82, INFO, Saving data for TFC by year\n",
+      "2024-10-23 21:22:11,144, data_manager.py, 82, INFO, Saving data for TFC by year\n",
+      "2024-10-23 21:22:12,155, data_manager.py, 73, INFO, Processing ticker TYL\n",
+      "2024-10-23 21:22:12,155, data_manager.py, 73, INFO, Processing ticker TYL\n",
+      "2024-10-23 21:22:12,157, data_manager.py, 108, INFO, Getting stock price data for TYL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:12,157, data_manager.py, 108, INFO, Getting stock price data for TYL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:12,416, data_manager.py, 82, INFO, Saving data for TYL by year\n",
+      "2024-10-23 21:22:12,416, data_manager.py, 82, INFO, Saving data for TYL by year\n",
+      "2024-10-23 21:22:13,374, data_manager.py, 73, INFO, Processing ticker TSN\n",
+      "2024-10-23 21:22:13,374, data_manager.py, 73, INFO, Processing ticker TSN\n",
+      "2024-10-23 21:22:13,375, data_manager.py, 108, INFO, Getting stock price data for TSN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:13,375, data_manager.py, 108, INFO, Getting stock price data for TSN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:13,744, data_manager.py, 82, INFO, Saving data for TSN by year\n",
+      "2024-10-23 21:22:13,744, data_manager.py, 82, INFO, Saving data for TSN by year\n",
+      "2024-10-23 21:22:14,755, data_manager.py, 73, INFO, Processing ticker USB\n",
+      "2024-10-23 21:22:14,755, data_manager.py, 73, INFO, Processing ticker USB\n",
+      "2024-10-23 21:22:14,756, data_manager.py, 108, INFO, Getting stock price data for USB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:14,756, data_manager.py, 108, INFO, Getting stock price data for USB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:15,068, data_manager.py, 82, INFO, Saving data for USB by year\n",
+      "2024-10-23 21:22:15,068, data_manager.py, 82, INFO, Saving data for USB by year\n",
+      "2024-10-23 21:22:16,034, data_manager.py, 73, INFO, Processing ticker UBER\n",
+      "2024-10-23 21:22:16,034, data_manager.py, 73, INFO, Processing ticker UBER\n",
+      "2024-10-23 21:22:16,035, data_manager.py, 108, INFO, Getting stock price data for UBER from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:16,035, data_manager.py, 108, INFO, Getting stock price data for UBER from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:16,163, data_manager.py, 82, INFO, Saving data for UBER by year\n",
+      "2024-10-23 21:22:16,163, data_manager.py, 82, INFO, Saving data for UBER by year\n",
+      "2024-10-23 21:22:16,424, data_manager.py, 73, INFO, Processing ticker UDR\n",
+      "2024-10-23 21:22:16,424, data_manager.py, 73, INFO, Processing ticker UDR\n",
+      "2024-10-23 21:22:16,426, data_manager.py, 108, INFO, Getting stock price data for UDR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:16,426, data_manager.py, 108, INFO, Getting stock price data for UDR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:16,687, data_manager.py, 82, INFO, Saving data for UDR by year\n",
+      "2024-10-23 21:22:16,687, data_manager.py, 82, INFO, Saving data for UDR by year\n",
+      "2024-10-23 21:22:17,767, data_manager.py, 73, INFO, Processing ticker ULTA\n",
+      "2024-10-23 21:22:17,767, data_manager.py, 73, INFO, Processing ticker ULTA\n",
+      "2024-10-23 21:22:17,769, data_manager.py, 108, INFO, Getting stock price data for ULTA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:17,769, data_manager.py, 108, INFO, Getting stock price data for ULTA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:17,931, data_manager.py, 82, INFO, Saving data for ULTA by year\n",
+      "2024-10-23 21:22:17,931, data_manager.py, 82, INFO, Saving data for ULTA by year\n",
+      "2024-10-23 21:22:18,676, data_manager.py, 73, INFO, Processing ticker UNP\n",
+      "2024-10-23 21:22:18,676, data_manager.py, 73, INFO, Processing ticker UNP\n",
+      "2024-10-23 21:22:18,677, data_manager.py, 108, INFO, Getting stock price data for UNP from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:18,677, data_manager.py, 108, INFO, Getting stock price data for UNP from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:18,987, data_manager.py, 82, INFO, Saving data for UNP by year\n",
+      "2024-10-23 21:22:18,987, data_manager.py, 82, INFO, Saving data for UNP by year\n",
+      "2024-10-23 21:22:20,032, data_manager.py, 73, INFO, Processing ticker UAL\n",
+      "2024-10-23 21:22:20,032, data_manager.py, 73, INFO, Processing ticker UAL\n",
+      "2024-10-23 21:22:20,034, data_manager.py, 108, INFO, Getting stock price data for UAL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:20,034, data_manager.py, 108, INFO, Getting stock price data for UAL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:20,243, data_manager.py, 82, INFO, Saving data for UAL by year\n",
+      "2024-10-23 21:22:20,243, data_manager.py, 82, INFO, Saving data for UAL by year\n",
+      "2024-10-23 21:22:20,997, data_manager.py, 73, INFO, Processing ticker UPS\n",
+      "2024-10-23 21:22:20,997, data_manager.py, 73, INFO, Processing ticker UPS\n",
+      "2024-10-23 21:22:20,998, data_manager.py, 108, INFO, Getting stock price data for UPS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:20,998, data_manager.py, 108, INFO, Getting stock price data for UPS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:21,610, data_manager.py, 82, INFO, Saving data for UPS by year\n",
+      "2024-10-23 21:22:21,610, data_manager.py, 82, INFO, Saving data for UPS by year\n",
+      "2024-10-23 21:22:22,695, data_manager.py, 73, INFO, Processing ticker URI\n",
+      "2024-10-23 21:22:22,695, data_manager.py, 73, INFO, Processing ticker URI\n",
+      "2024-10-23 21:22:22,696, data_manager.py, 108, INFO, Getting stock price data for URI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:22,696, data_manager.py, 108, INFO, Getting stock price data for URI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:23,039, data_manager.py, 82, INFO, Saving data for URI by year\n",
+      "2024-10-23 21:22:23,039, data_manager.py, 82, INFO, Saving data for URI by year\n",
+      "2024-10-23 21:22:24,233, data_manager.py, 73, INFO, Processing ticker UNH\n",
+      "2024-10-23 21:22:24,233, data_manager.py, 73, INFO, Processing ticker UNH\n",
+      "2024-10-23 21:22:24,234, data_manager.py, 108, INFO, Getting stock price data for UNH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:24,234, data_manager.py, 108, INFO, Getting stock price data for UNH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:24,637, data_manager.py, 82, INFO, Saving data for UNH by year\n",
+      "2024-10-23 21:22:24,637, data_manager.py, 82, INFO, Saving data for UNH by year\n",
+      "2024-10-23 21:22:46,753, data_manager.py, 73, INFO, Processing ticker UHS\n",
+      "2024-10-23 21:22:46,753, data_manager.py, 73, INFO, Processing ticker UHS\n",
+      "2024-10-23 21:22:25,722, data_manager.py, 108, INFO, Getting stock price data for UHS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:25,722, data_manager.py, 108, INFO, Getting stock price data for UHS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:26,136, data_manager.py, 82, INFO, Saving data for UHS by year\n",
+      "2024-10-23 21:22:26,136, data_manager.py, 82, INFO, Saving data for UHS by year\n",
+      "2024-10-23 21:22:27,163, data_manager.py, 73, INFO, Processing ticker VLO\n",
+      "2024-10-23 21:22:27,163, data_manager.py, 73, INFO, Processing ticker VLO\n",
+      "2024-10-23 21:22:27,164, data_manager.py, 108, INFO, Getting stock price data for VLO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:27,164, data_manager.py, 108, INFO, Getting stock price data for VLO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:27,587, data_manager.py, 82, INFO, Saving data for VLO by year\n",
+      "2024-10-23 21:22:27,587, data_manager.py, 82, INFO, Saving data for VLO by year\n",
+      "2024-10-23 21:22:28,566, data_manager.py, 73, INFO, Processing ticker VTR\n",
+      "2024-10-23 21:22:28,566, data_manager.py, 73, INFO, Processing ticker VTR\n",
+      "2024-10-23 21:22:28,568, data_manager.py, 108, INFO, Getting stock price data for VTR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:28,568, data_manager.py, 108, INFO, Getting stock price data for VTR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:29,102, data_manager.py, 82, INFO, Saving data for VTR by year\n",
+      "2024-10-23 21:22:29,102, data_manager.py, 82, INFO, Saving data for VTR by year\n",
+      "2024-10-23 21:22:30,063, data_manager.py, 73, INFO, Processing ticker VLTO\n",
+      "2024-10-23 21:22:30,063, data_manager.py, 73, INFO, Processing ticker VLTO\n",
+      "2024-10-23 21:22:30,064, data_manager.py, 108, INFO, Getting stock price data for VLTO from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:30,064, data_manager.py, 108, INFO, Getting stock price data for VLTO from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:30,150, data_manager.py, 82, INFO, Saving data for VLTO by year\n",
+      "2024-10-23 21:22:30,150, data_manager.py, 82, INFO, Saving data for VLTO by year\n",
+      "2024-10-23 21:22:30,237, data_manager.py, 73, INFO, Processing ticker VRSN\n",
+      "2024-10-23 21:22:30,237, data_manager.py, 73, INFO, Processing ticker VRSN\n",
+      "2024-10-23 21:22:30,239, data_manager.py, 108, INFO, Getting stock price data for VRSN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:30,239, data_manager.py, 108, INFO, Getting stock price data for VRSN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:30,543, data_manager.py, 82, INFO, Saving data for VRSN by year\n",
+      "2024-10-23 21:22:30,543, data_manager.py, 82, INFO, Saving data for VRSN by year\n",
+      "2024-10-23 21:22:31,467, data_manager.py, 73, INFO, Processing ticker VRSK\n",
+      "2024-10-23 21:22:31,467, data_manager.py, 73, INFO, Processing ticker VRSK\n",
+      "2024-10-23 21:22:31,468, data_manager.py, 108, INFO, Getting stock price data for VRSK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:31,468, data_manager.py, 108, INFO, Getting stock price data for VRSK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:31,726, data_manager.py, 82, INFO, Saving data for VRSK by year\n",
+      "2024-10-23 21:22:31,726, data_manager.py, 82, INFO, Saving data for VRSK by year\n",
+      "2024-10-23 21:22:32,368, data_manager.py, 73, INFO, Processing ticker VZ\n",
+      "2024-10-23 21:22:32,368, data_manager.py, 73, INFO, Processing ticker VZ\n",
+      "2024-10-23 21:22:32,369, data_manager.py, 108, INFO, Getting stock price data for VZ from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:32,369, data_manager.py, 108, INFO, Getting stock price data for VZ from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:32,734, data_manager.py, 82, INFO, Saving data for VZ by year\n",
+      "2024-10-23 21:22:32,734, data_manager.py, 82, INFO, Saving data for VZ by year\n",
+      "2024-10-23 21:22:33,742, data_manager.py, 73, INFO, Processing ticker VRTX\n",
+      "2024-10-23 21:22:33,742, data_manager.py, 73, INFO, Processing ticker VRTX\n",
+      "2024-10-23 21:22:33,743, data_manager.py, 108, INFO, Getting stock price data for VRTX from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:33,743, data_manager.py, 108, INFO, Getting stock price data for VRTX from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:34,021, data_manager.py, 82, INFO, Saving data for VRTX by year\n",
+      "2024-10-23 21:22:34,021, data_manager.py, 82, INFO, Saving data for VRTX by year\n",
+      "2024-10-23 21:22:35,113, data_manager.py, 73, INFO, Processing ticker VFC\n",
+      "2024-10-23 21:22:35,113, data_manager.py, 73, INFO, Processing ticker VFC\n",
+      "2024-10-23 21:22:35,114, data_manager.py, 108, INFO, Getting stock price data for VFC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:35,114, data_manager.py, 108, INFO, Getting stock price data for VFC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:35,526, data_manager.py, 82, INFO, Saving data for VFC by year\n",
+      "2024-10-23 21:22:35,526, data_manager.py, 82, INFO, Saving data for VFC by year\n",
+      "2024-10-23 21:22:36,474, data_manager.py, 73, INFO, Processing ticker VTRS\n",
+      "2024-10-23 21:22:36,474, data_manager.py, 73, INFO, Processing ticker VTRS\n",
+      "2024-10-23 21:22:36,475, data_manager.py, 108, INFO, Getting stock price data for VTRS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:36,475, data_manager.py, 108, INFO, Getting stock price data for VTRS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:36,844, data_manager.py, 82, INFO, Saving data for VTRS by year\n",
+      "2024-10-23 21:22:36,844, data_manager.py, 82, INFO, Saving data for VTRS by year\n",
+      "2024-10-23 21:22:37,801, data_manager.py, 73, INFO, Processing ticker VICI\n",
+      "2024-10-23 21:22:37,801, data_manager.py, 73, INFO, Processing ticker VICI\n",
+      "2024-10-23 21:22:37,802, data_manager.py, 108, INFO, Getting stock price data for VICI from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:37,802, data_manager.py, 108, INFO, Getting stock price data for VICI from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:38,039, data_manager.py, 82, INFO, Saving data for VICI by year\n",
+      "2024-10-23 21:22:38,039, data_manager.py, 82, INFO, Saving data for VICI by year\n",
+      "2024-10-23 21:22:38,279, data_manager.py, 73, INFO, Processing ticker V\n",
+      "2024-10-23 21:22:38,279, data_manager.py, 73, INFO, Processing ticker V\n",
+      "2024-10-23 21:22:38,280, data_manager.py, 108, INFO, Getting stock price data for V from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:38,280, data_manager.py, 108, INFO, Getting stock price data for V from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:38,718, data_manager.py, 82, INFO, Saving data for V by year\n",
+      "2024-10-23 21:22:38,718, data_manager.py, 82, INFO, Saving data for V by year\n",
+      "2024-10-23 21:22:39,442, data_manager.py, 73, INFO, Processing ticker VMC\n",
+      "2024-10-23 21:22:39,442, data_manager.py, 73, INFO, Processing ticker VMC\n",
+      "2024-10-23 21:22:39,444, data_manager.py, 108, INFO, Getting stock price data for VMC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:39,444, data_manager.py, 108, INFO, Getting stock price data for VMC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:39,994, data_manager.py, 82, INFO, Saving data for VMC by year\n",
+      "2024-10-23 21:22:39,994, data_manager.py, 82, INFO, Saving data for VMC by year\n",
+      "2024-10-23 21:22:40,848, data_manager.py, 73, INFO, Processing ticker WRB\n",
+      "2024-10-23 21:22:40,848, data_manager.py, 73, INFO, Processing ticker WRB\n",
+      "2024-10-23 21:22:40,850, data_manager.py, 108, INFO, Getting stock price data for WRB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:40,850, data_manager.py, 108, INFO, Getting stock price data for WRB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:41,490, data_manager.py, 82, INFO, Saving data for WRB by year\n",
+      "2024-10-23 21:22:41,490, data_manager.py, 82, INFO, Saving data for WRB by year\n",
+      "2024-10-23 21:22:42,418, data_manager.py, 73, INFO, Processing ticker WAB\n",
+      "2024-10-23 21:22:42,418, data_manager.py, 73, INFO, Processing ticker WAB\n",
+      "2024-10-23 21:22:42,420, data_manager.py, 108, INFO, Getting stock price data for WAB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:42,420, data_manager.py, 108, INFO, Getting stock price data for WAB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:42,789, data_manager.py, 82, INFO, Saving data for WAB by year\n",
+      "2024-10-23 21:22:42,789, data_manager.py, 82, INFO, Saving data for WAB by year\n",
+      "2024-10-23 21:22:43,929, data_manager.py, 73, INFO, Processing ticker WBA\n",
+      "2024-10-23 21:22:43,929, data_manager.py, 73, INFO, Processing ticker WBA\n",
+      "2024-10-23 21:22:43,930, data_manager.py, 108, INFO, Getting stock price data for WBA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:43,930, data_manager.py, 108, INFO, Getting stock price data for WBA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:44,351, data_manager.py, 82, INFO, Saving data for WBA by year\n",
+      "2024-10-23 21:22:44,351, data_manager.py, 82, INFO, Saving data for WBA by year\n",
+      "2024-10-23 21:22:45,612, data_manager.py, 73, INFO, Processing ticker WMT\n",
+      "2024-10-23 21:22:45,612, data_manager.py, 73, INFO, Processing ticker WMT\n",
+      "2024-10-23 21:22:45,613, data_manager.py, 108, INFO, Getting stock price data for WMT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:45,613, data_manager.py, 108, INFO, Getting stock price data for WMT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:45,999, data_manager.py, 82, INFO, Saving data for WMT by year\n",
+      "2024-10-23 21:22:45,999, data_manager.py, 82, INFO, Saving data for WMT by year\n",
+      "2024-10-23 21:22:47,050, data_manager.py, 73, INFO, Processing ticker DIS\n",
+      "2024-10-23 21:22:47,050, data_manager.py, 73, INFO, Processing ticker DIS\n",
+      "2024-10-23 21:22:47,052, data_manager.py, 108, INFO, Getting stock price data for DIS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:47,052, data_manager.py, 108, INFO, Getting stock price data for DIS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:47,678, data_manager.py, 82, INFO, Saving data for DIS by year\n",
+      "2024-10-23 21:22:47,678, data_manager.py, 82, INFO, Saving data for DIS by year\n",
+      "2024-10-23 21:22:48,622, data_manager.py, 73, INFO, Processing ticker WBD\n",
+      "2024-10-23 21:22:48,622, data_manager.py, 73, INFO, Processing ticker WBD\n",
+      "2024-10-23 21:22:48,623, data_manager.py, 108, INFO, Getting stock price data for WBD from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:48,623, data_manager.py, 108, INFO, Getting stock price data for WBD from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:48,960, data_manager.py, 82, INFO, Saving data for WBD by year\n",
+      "2024-10-23 21:22:48,960, data_manager.py, 82, INFO, Saving data for WBD by year\n",
+      "2024-10-23 21:22:49,712, data_manager.py, 73, INFO, Processing ticker WM\n",
+      "2024-10-23 21:22:49,712, data_manager.py, 73, INFO, Processing ticker WM\n",
+      "2024-10-23 21:22:49,714, data_manager.py, 108, INFO, Getting stock price data for WM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:49,714, data_manager.py, 108, INFO, Getting stock price data for WM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:50,072, data_manager.py, 82, INFO, Saving data for WM by year\n",
+      "2024-10-23 21:22:50,072, data_manager.py, 82, INFO, Saving data for WM by year\n",
+      "2024-10-23 21:22:50,978, data_manager.py, 73, INFO, Processing ticker WAT\n",
+      "2024-10-23 21:22:50,978, data_manager.py, 73, INFO, Processing ticker WAT\n",
+      "2024-10-23 21:22:50,979, data_manager.py, 108, INFO, Getting stock price data for WAT from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:50,979, data_manager.py, 108, INFO, Getting stock price data for WAT from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:51,364, data_manager.py, 82, INFO, Saving data for WAT by year\n",
+      "2024-10-23 21:22:51,364, data_manager.py, 82, INFO, Saving data for WAT by year\n",
+      "2024-10-23 21:22:52,405, data_manager.py, 73, INFO, Processing ticker WEC\n",
+      "2024-10-23 21:22:52,405, data_manager.py, 73, INFO, Processing ticker WEC\n",
+      "2024-10-23 21:22:52,407, data_manager.py, 108, INFO, Getting stock price data for WEC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:52,407, data_manager.py, 108, INFO, Getting stock price data for WEC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:52,907, data_manager.py, 82, INFO, Saving data for WEC by year\n",
+      "2024-10-23 21:22:52,907, data_manager.py, 82, INFO, Saving data for WEC by year\n",
+      "2024-10-23 21:22:53,932, data_manager.py, 73, INFO, Processing ticker WFC\n",
+      "2024-10-23 21:22:53,932, data_manager.py, 73, INFO, Processing ticker WFC\n",
+      "2024-10-23 21:22:53,934, data_manager.py, 108, INFO, Getting stock price data for WFC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:53,934, data_manager.py, 108, INFO, Getting stock price data for WFC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:54,481, data_manager.py, 82, INFO, Saving data for WFC by year\n",
+      "2024-10-23 21:22:54,481, data_manager.py, 82, INFO, Saving data for WFC by year\n",
+      "2024-10-23 21:22:55,452, data_manager.py, 73, INFO, Processing ticker WELL\n",
+      "2024-10-23 21:22:55,452, data_manager.py, 73, INFO, Processing ticker WELL\n",
+      "2024-10-23 21:22:55,453, data_manager.py, 108, INFO, Getting stock price data for WELL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:55,453, data_manager.py, 108, INFO, Getting stock price data for WELL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:55,959, data_manager.py, 82, INFO, Saving data for WELL by year\n",
+      "2024-10-23 21:22:55,959, data_manager.py, 82, INFO, Saving data for WELL by year\n",
+      "2024-10-23 21:22:57,037, data_manager.py, 73, INFO, Processing ticker WST\n",
+      "2024-10-23 21:22:57,037, data_manager.py, 73, INFO, Processing ticker WST\n",
+      "2024-10-23 21:22:57,039, data_manager.py, 108, INFO, Getting stock price data for WST from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:57,039, data_manager.py, 108, INFO, Getting stock price data for WST from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:57,567, data_manager.py, 82, INFO, Saving data for WST by year\n",
+      "2024-10-23 21:22:57,567, data_manager.py, 82, INFO, Saving data for WST by year\n",
+      "2024-10-23 21:22:58,483, data_manager.py, 73, INFO, Processing ticker WDC\n",
+      "2024-10-23 21:22:58,483, data_manager.py, 73, INFO, Processing ticker WDC\n",
+      "2024-10-23 21:22:58,485, data_manager.py, 108, INFO, Getting stock price data for WDC from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:58,485, data_manager.py, 108, INFO, Getting stock price data for WDC from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:22:58,882, data_manager.py, 82, INFO, Saving data for WDC by year\n",
+      "2024-10-23 21:22:58,882, data_manager.py, 82, INFO, Saving data for WDC by year\n",
+      "2024-10-23 21:22:59,772, data_manager.py, 73, INFO, Processing ticker WRK\n",
+      "2024-10-23 21:22:59,772, data_manager.py, 73, INFO, Processing ticker WRK\n",
+      "2024-10-23 21:22:59,773, data_manager.py, 108, INFO, Getting stock price data for WRK from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:22:59,773, data_manager.py, 108, INFO, Getting stock price data for WRK from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "\n",
+      "1 Failed download:\n",
+      "['WRK']: YFTzMissingError('$%ticker%: possibly delisted; No timezone found')\n",
+      "2024-10-23 21:23:01,176, data_manager.py, 82, INFO, Saving data for WRK by year\n",
+      "2024-10-23 21:23:01,176, data_manager.py, 82, INFO, Saving data for WRK by year\n",
+      "2024-10-23 21:23:01,178, data_manager.py, 100, WARNING, No data found for WRK\n",
+      "2024-10-23 21:23:01,178, data_manager.py, 100, WARNING, No data found for WRK\n",
+      "2024-10-23 21:23:01,179, data_manager.py, 73, INFO, Processing ticker WY\n",
+      "2024-10-23 21:23:01,179, data_manager.py, 73, INFO, Processing ticker WY\n",
+      "2024-10-23 21:23:01,181, data_manager.py, 108, INFO, Getting stock price data for WY from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:01,181, data_manager.py, 108, INFO, Getting stock price data for WY from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:01,557, data_manager.py, 82, INFO, Saving data for WY by year\n",
+      "2024-10-23 21:23:01,557, data_manager.py, 82, INFO, Saving data for WY by year\n",
+      "2024-10-23 21:23:02,596, data_manager.py, 73, INFO, Processing ticker WHR\n",
+      "2024-10-23 21:23:02,596, data_manager.py, 73, INFO, Processing ticker WHR\n",
+      "2024-10-23 21:23:02,598, data_manager.py, 108, INFO, Getting stock price data for WHR from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:02,598, data_manager.py, 108, INFO, Getting stock price data for WHR from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:02,971, data_manager.py, 82, INFO, Saving data for WHR by year\n",
+      "2024-10-23 21:23:02,971, data_manager.py, 82, INFO, Saving data for WHR by year\n",
+      "2024-10-23 21:23:03,945, data_manager.py, 73, INFO, Processing ticker WMB\n",
+      "2024-10-23 21:23:03,945, data_manager.py, 73, INFO, Processing ticker WMB\n",
+      "2024-10-23 21:23:03,947, data_manager.py, 108, INFO, Getting stock price data for WMB from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:03,947, data_manager.py, 108, INFO, Getting stock price data for WMB from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:04,510, data_manager.py, 82, INFO, Saving data for WMB by year\n",
+      "2024-10-23 21:23:04,510, data_manager.py, 82, INFO, Saving data for WMB by year\n",
+      "2024-10-23 21:23:05,427, data_manager.py, 73, INFO, Processing ticker WTW\n",
+      "2024-10-23 21:23:05,427, data_manager.py, 73, INFO, Processing ticker WTW\n",
+      "2024-10-23 21:23:05,428, data_manager.py, 108, INFO, Getting stock price data for WTW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:05,428, data_manager.py, 108, INFO, Getting stock price data for WTW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:26,837, data_manager.py, 82, INFO, Saving data for WTW by year\n",
+      "2024-10-23 21:23:26,837, data_manager.py, 82, INFO, Saving data for WTW by year\n",
+      "2024-10-23 21:23:06,716, data_manager.py, 73, INFO, Processing ticker GWW\n",
+      "2024-10-23 21:23:06,716, data_manager.py, 73, INFO, Processing ticker GWW\n",
+      "2024-10-23 21:23:06,718, data_manager.py, 108, INFO, Getting stock price data for GWW from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:06,718, data_manager.py, 108, INFO, Getting stock price data for GWW from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:07,141, data_manager.py, 82, INFO, Saving data for GWW by year\n",
+      "2024-10-23 21:23:07,141, data_manager.py, 82, INFO, Saving data for GWW by year\n",
+      "2024-10-23 21:23:08,089, data_manager.py, 73, INFO, Processing ticker WYNN\n",
+      "2024-10-23 21:23:08,089, data_manager.py, 73, INFO, Processing ticker WYNN\n",
+      "2024-10-23 21:23:08,091, data_manager.py, 108, INFO, Getting stock price data for WYNN from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:08,091, data_manager.py, 108, INFO, Getting stock price data for WYNN from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:08,411, data_manager.py, 82, INFO, Saving data for WYNN by year\n",
+      "2024-10-23 21:23:08,411, data_manager.py, 82, INFO, Saving data for WYNN by year\n",
+      "2024-10-23 21:23:09,194, data_manager.py, 73, INFO, Processing ticker XEL\n",
+      "2024-10-23 21:23:09,194, data_manager.py, 73, INFO, Processing ticker XEL\n",
+      "2024-10-23 21:23:09,195, data_manager.py, 108, INFO, Getting stock price data for XEL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:09,195, data_manager.py, 108, INFO, Getting stock price data for XEL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:09,645, data_manager.py, 82, INFO, Saving data for XEL by year\n",
+      "2024-10-23 21:23:09,645, data_manager.py, 82, INFO, Saving data for XEL by year\n",
+      "2024-10-23 21:23:10,598, data_manager.py, 73, INFO, Processing ticker XYL\n",
+      "2024-10-23 21:23:10,598, data_manager.py, 73, INFO, Processing ticker XYL\n",
+      "2024-10-23 21:23:10,599, data_manager.py, 108, INFO, Getting stock price data for XYL from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:10,599, data_manager.py, 108, INFO, Getting stock price data for XYL from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:31,939, data_manager.py, 82, INFO, Saving data for XYL by year\n",
+      "2024-10-23 21:23:31,939, data_manager.py, 82, INFO, Saving data for XYL by year\n",
+      "2024-10-23 21:23:11,430, data_manager.py, 73, INFO, Processing ticker YUM\n",
+      "2024-10-23 21:23:11,430, data_manager.py, 73, INFO, Processing ticker YUM\n",
+      "2024-10-23 21:23:11,431, data_manager.py, 108, INFO, Getting stock price data for YUM from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:11,431, data_manager.py, 108, INFO, Getting stock price data for YUM from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:11,876, data_manager.py, 82, INFO, Saving data for YUM by year\n",
+      "2024-10-23 21:23:11,876, data_manager.py, 82, INFO, Saving data for YUM by year\n",
+      "2024-10-23 21:23:12,954, data_manager.py, 73, INFO, Processing ticker ZBRA\n",
+      "2024-10-23 21:23:12,954, data_manager.py, 73, INFO, Processing ticker ZBRA\n",
+      "2024-10-23 21:23:12,955, data_manager.py, 108, INFO, Getting stock price data for ZBRA from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:12,955, data_manager.py, 108, INFO, Getting stock price data for ZBRA from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:13,336, data_manager.py, 82, INFO, Saving data for ZBRA by year\n",
+      "2024-10-23 21:23:13,336, data_manager.py, 82, INFO, Saving data for ZBRA by year\n",
+      "2024-10-23 21:23:14,293, data_manager.py, 73, INFO, Processing ticker ZBH\n",
+      "2024-10-23 21:23:14,293, data_manager.py, 73, INFO, Processing ticker ZBH\n",
+      "2024-10-23 21:23:14,295, data_manager.py, 108, INFO, Getting stock price data for ZBH from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:14,295, data_manager.py, 108, INFO, Getting stock price data for ZBH from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:14,625, data_manager.py, 82, INFO, Saving data for ZBH by year\n",
+      "2024-10-23 21:23:14,625, data_manager.py, 82, INFO, Saving data for ZBH by year\n",
+      "2024-10-23 21:23:15,565, data_manager.py, 73, INFO, Processing ticker ZION\n",
+      "2024-10-23 21:23:15,565, data_manager.py, 73, INFO, Processing ticker ZION\n",
+      "2024-10-23 21:23:15,567, data_manager.py, 108, INFO, Getting stock price data for ZION from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:15,567, data_manager.py, 108, INFO, Getting stock price data for ZION from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:37,010, data_manager.py, 82, INFO, Saving data for ZION by year\n",
+      "2024-10-23 21:23:37,010, data_manager.py, 82, INFO, Saving data for ZION by year\n",
+      "2024-10-23 21:23:16,991, data_manager.py, 73, INFO, Processing ticker ZTS\n",
+      "2024-10-23 21:23:16,991, data_manager.py, 73, INFO, Processing ticker ZTS\n",
+      "2024-10-23 21:23:16,992, data_manager.py, 108, INFO, Getting stock price data for ZTS from 2000-01-01 to 2024-10-23\n",
+      "2024-10-23 21:23:16,992, data_manager.py, 108, INFO, Getting stock price data for ZTS from 2000-01-01 to 2024-10-23\n",
+      "[*********************100%%**********************]  1 of 1 completed\n",
+      "2024-10-23 21:23:17,250, data_manager.py, 82, INFO, Saving data for ZTS by year\n",
+      "2024-10-23 21:23:17,250, data_manager.py, 82, INFO, Saving data for ZTS by year\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "dm.download_all()"
@@ -609,9 +4788,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-23 21:23:17,666, data_manager.py, 117, INFO, Creating features data.\n",
+      "2024-10-23 21:23:17,666, data_manager.py, 117, INFO, Creating features data.\n",
+      "2024-10-23 21:23:17,667, data_manager.py, 128, INFO, Loading price data from ../../05_src/data/prices/\n",
+      "2024-10-23 21:23:17,667, data_manager.py, 128, INFO, Loading price data from ../../05_src/data/prices/\n",
+      "/home/alex8642/miniconda3/envs/dsi_participant/lib/python3.9/site-packages/dask/dataframe/core.py:5517: UserWarning: New index has same name as existing, this is a no-op.\n",
+      "  warnings.warn(\n",
+      "2024-10-23 21:23:18,131, data_manager.py, 136, INFO, Creating features\n",
+      "2024-10-23 21:23:18,131, data_manager.py, 136, INFO, Creating features\n",
+      "/home/alex8642/dsi/production/01_materials/labs/../../05_src/data_manager.py:138: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .apply(func)\n",
+      "  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .apply(func, meta=('x', 'f8'))            for series result\n",
+      "  features = (price_dd\n",
+      "2024-10-23 21:23:18,314, data_manager.py, 154, INFO, Creating target\n",
+      "2024-10-23 21:23:18,314, data_manager.py, 154, INFO, Creating target\n",
+      "/home/alex8642/dsi/production/01_materials/labs/../../05_src/data_manager.py:155: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .apply(func)\n",
+      "  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .apply(func, meta=('x', 'f8'))            for series result\n",
+      "  self.features = (self.features.groupby('ticker', group_keys=False).apply(\n",
+      "2024-10-23 21:23:18,364, data_manager.py, 164, INFO, Saving features to ../../05_src/data/features/stock_features.parquet\n",
+      "2024-10-23 21:23:18,364, data_manager.py, 164, INFO, Saving features to ../../05_src/data/features/stock_features.parquet\n"
+     ]
+    }
+   ],
    "source": [
     "dm.featurize()"
    ]
@@ -619,7 +4827,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "env",
+   "display_name": "dsi_participant",
    "language": "python",
    "name": "python3"
   },
@@ -633,7 +4841,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/01_materials/labs/03a_sampling.ipynb b/01_materials/labs/03a_sampling.ipynb
index 6207aa9d9..44125d2ac 100644
--- a/01_materials/labs/03a_sampling.ipynb
+++ b/01_materials/labs/03a_sampling.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,9 +17,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1945/1500862777.py:1: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \n",
+      "In a future release, Dask DataFrame will use new implementation that\n",
+      "contains several improvements including a logical query planning.\n",
+      "The user-facing DataFrame API will remain unchanged.\n",
+      "\n",
+      "The new implementation is already available and can be enabled by\n",
+      "installing the dask-expr library:\n",
+      "\n",
+      "    $ pip install dask-expr\n",
+      "\n",
+      "and turning the query planning option on:\n",
+      "\n",
+      "    >>> import dask\n",
+      "    >>> dask.config.set({'dataframe.query-planning': True})\n",
+      "    >>> import dask.dataframe as dd\n",
+      "\n",
+      "API documentation for the new implementation is available at\n",
+      "https://docs.dask.org/en/stable/dask-expr-api.html\n",
+      "\n",
+      "Any feedback can be reported on the Dask issue tracker\n",
+      "https://github.com/dask/dask/issues \n",
+      "\n",
+      "  import dask.dataframe as dd\n"
+     ]
+    }
+   ],
    "source": [
     "import dask.dataframe as dd\n",
     "import pandas as pd\n",
@@ -30,7 +60,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,18 +102,197 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ticker</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>sector</th>\n",
+       "      <th>subsector</th>\n",
+       "      <th>year</th>\n",
+       "      <th>Close_lag_1</th>\n",
+       "      <th>returns</th>\n",
+       "      <th>positive_return</th>\n",
+       "      <th>target</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>636458</th>\n",
+       "      <td>PAYC</td>\n",
+       "      <td>2022-10-10</td>\n",
+       "      <td>339.200012</td>\n",
+       "      <td>339.200012</td>\n",
+       "      <td>316.869995</td>\n",
+       "      <td>323.980011</td>\n",
+       "      <td>320.343262</td>\n",
+       "      <td>368200</td>\n",
+       "      <td>Industrials</td>\n",
+       "      <td>Human Resource &amp; Employment Services</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>338.399994</td>\n",
+       "      <td>-0.042612</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>217236</th>\n",
+       "      <td>KEYS</td>\n",
+       "      <td>2023-12-13</td>\n",
+       "      <td>149.460007</td>\n",
+       "      <td>153.070007</td>\n",
+       "      <td>148.759995</td>\n",
+       "      <td>152.309998</td>\n",
+       "      <td>152.309998</td>\n",
+       "      <td>2120200</td>\n",
+       "      <td>Information Technology</td>\n",
+       "      <td>Electronic Equipment &amp; Instruments</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>149.369995</td>\n",
+       "      <td>0.019683</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>739262</th>\n",
+       "      <td>AWK</td>\n",
+       "      <td>2012-10-18</td>\n",
+       "      <td>37.290001</td>\n",
+       "      <td>37.430000</td>\n",
+       "      <td>37.060001</td>\n",
+       "      <td>37.270000</td>\n",
+       "      <td>29.126347</td>\n",
+       "      <td>616100</td>\n",
+       "      <td>Utilities</td>\n",
+       "      <td>Water Utilities</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>37.299999</td>\n",
+       "      <td>-0.000804</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>219650</th>\n",
+       "      <td>DVA</td>\n",
+       "      <td>2008-09-30</td>\n",
+       "      <td>27.850000</td>\n",
+       "      <td>28.549999</td>\n",
+       "      <td>27.355000</td>\n",
+       "      <td>28.504999</td>\n",
+       "      <td>28.504999</td>\n",
+       "      <td>2650400</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Health Care Services</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>27.500000</td>\n",
+       "      <td>0.036545</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>633338</th>\n",
+       "      <td>PLD</td>\n",
+       "      <td>2020-11-24</td>\n",
+       "      <td>100.379997</td>\n",
+       "      <td>100.730003</td>\n",
+       "      <td>98.529999</td>\n",
+       "      <td>98.809998</td>\n",
+       "      <td>89.209778</td>\n",
+       "      <td>2746400</td>\n",
+       "      <td>Real Estate</td>\n",
+       "      <td>Industrial REITs</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>99.559998</td>\n",
+       "      <td>-0.007533</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       ticker       Date        Open        High         Low       Close  \\\n",
+       "636458   PAYC 2022-10-10  339.200012  339.200012  316.869995  323.980011   \n",
+       "217236   KEYS 2023-12-13  149.460007  153.070007  148.759995  152.309998   \n",
+       "739262    AWK 2012-10-18   37.290001   37.430000   37.060001   37.270000   \n",
+       "219650    DVA 2008-09-30   27.850000   28.549999   27.355000   28.504999   \n",
+       "633338    PLD 2020-11-24  100.379997  100.730003   98.529999   98.809998   \n",
+       "\n",
+       "         Adj Close   Volume                  sector  \\\n",
+       "636458  320.343262   368200             Industrials   \n",
+       "217236  152.309998  2120200  Information Technology   \n",
+       "739262   29.126347   616100               Utilities   \n",
+       "219650   28.504999  2650400             Health Care   \n",
+       "633338   89.209778  2746400             Real Estate   \n",
+       "\n",
+       "                                   subsector  year  Close_lag_1   returns  \\\n",
+       "636458  Human Resource & Employment Services  2022   338.399994 -0.042612   \n",
+       "217236    Electronic Equipment & Instruments  2023   149.369995  0.019683   \n",
+       "739262                       Water Utilities  2012    37.299999 -0.000804   \n",
+       "219650                  Health Care Services  2008    27.500000  0.036545   \n",
+       "633338                      Industrial REITs  2020    99.559998 -0.007533   \n",
+       "\n",
+       "        positive_return  target  \n",
+       "636458                0     0.0  \n",
+       "217236                1     1.0  \n",
+       "739262                0     1.0  \n",
+       "219650                1     0.0  \n",
+       "633338                0     1.0  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df.sample(n = 5)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['OXY', 'TXN', 'PCG', 'CBRE', 'ROK', 'AMT', 'D', 'YUM', 'PWR']"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# select_tickers = df['ticker'].unique().tolist()[0:9]\n",
     "select_tickers = ['OXY', 'TXN', 'PCG', 'CBRE', 'ROK', 'AMT', 'D', 'YUM', 'PWR']\n",
@@ -92,9 +301,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((5506, 15), (55055, 15))"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "idx = df['ticker'].isin(select_tickers)\n",
     "small_df = df[idx]\n",
@@ -111,18 +331,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='ticker'>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "small_df['ticker'].value_counts().plot(kind='bar')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='ticker'>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "simple_sample_dt['ticker'].value_counts().plot(kind='bar')"
    ]
@@ -138,9 +400,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='ticker'>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "strat_sample_dt = small_df.groupby(['ticker']).sample(frac = 0.1)\n",
     "strat_sample_dt['ticker'].value_counts().plot(kind='bar')"
@@ -157,9 +440,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1945/2932236319.py:2: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .apply(func)\n",
+      "  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .apply(func, meta=('x', 'f8'))            for series result\n",
+      "  strat_sample_dd_dt = (dd_dt\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='ticker'>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "dd_dt = dd.read_parquet(ft_glob)\n",
     "strat_sample_dd_dt = (dd_dt\n",
@@ -173,7 +488,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "env",
+   "display_name": "dsi_participant",
    "language": "python",
    "name": "python3"
   },
@@ -187,7 +502,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/01_materials/labs/03b_pipeline.ipynb b/01_materials/labs/03b_pipeline.ipynb
index f1027ef62..703fa143a 100644
--- a/01_materials/labs/03b_pipeline.ipynb
+++ b/01_materials/labs/03b_pipeline.ipynb
@@ -9,9 +9,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_18392/4071503124.py:6: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \n",
+      "In a future release, Dask DataFrame will use new implementation that\n",
+      "contains several improvements including a logical query planning.\n",
+      "The user-facing DataFrame API will remain unchanged.\n",
+      "\n",
+      "The new implementation is already available and can be enabled by\n",
+      "installing the dask-expr library:\n",
+      "\n",
+      "    $ pip install dask-expr\n",
+      "\n",
+      "and turning the query planning option on:\n",
+      "\n",
+      "    >>> import dask\n",
+      "    >>> dask.config.set({'dataframe.query-planning': True})\n",
+      "    >>> import dask.dataframe as dd\n",
+      "\n",
+      "API documentation for the new implementation is available at\n",
+      "https://docs.dask.org/en/stable/dask-expr-api.html\n",
+      "\n",
+      "Any feedback can be reported on the Dask issue tracker\n",
+      "https://github.com/dask/dask/issues \n",
+      "\n",
+      "  import dask.dataframe as dd\n"
+     ]
+    }
+   ],
    "source": [
     "%load_ext dotenv\n",
     "%dotenv \n",
@@ -63,9 +93,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>returns</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>2.776708e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>4.539163e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>3.769205e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-9.982798e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-9.133833e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>5.048071e-04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1.018515e-02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>2.498020e+02</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            returns\n",
+       "count  2.776708e+06\n",
+       "mean   4.539163e-03\n",
+       "std    3.769205e-01\n",
+       "min   -9.982798e-01\n",
+       "25%   -9.133833e-03\n",
+       "50%    5.048071e-04\n",
+       "75%    1.018515e-02\n",
+       "max    2.498020e+02"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "returns = df[[ 'returns']].dropna()\n",
     "returns.describe()"
@@ -73,9 +181,427 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>StandardScaler()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "StandardScaler()"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Create a StandardScaler object\n",
     "\n",
@@ -89,9 +615,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>returns</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>2.776708e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-6.750482e-18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>1.000000e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-2.660559e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-3.627555e-02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-1.070347e-02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1.497926e-02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>6.627326e+02</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            returns\n",
+       "count  2.776708e+06\n",
+       "mean  -6.750482e-18\n",
+       "std    1.000000e+00\n",
+       "min   -2.660559e+00\n",
+       "25%   -3.627555e-02\n",
+       "50%   -1.070347e-02\n",
+       "75%    1.497926e-02\n",
+       "max    6.627326e+02"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Transform the returns data using the fitted scaler\n",
     "\n",
@@ -111,9 +715,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='sector'>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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sFkJERESks1gIERERkc5iIUREREQ6i4UQERER6SwWQkRERKSzWAgRERGRzmIhRERERDqrWoXQ+vXr0bFjR5iamsLU1BQ9evTAr7/+Kp0XQmDhwoWwtraGkZERXn75ZZw9e1brMQoLCzFt2jSYm5vD2NgYQ4cOxbVr17Ta5OTkwNvbGxqNBhqNBt7e3rh9+7ZWm/T0dAwZMgTGxsYwNzeHn58fioqKtNokJiaid+/eMDIyQvPmzbF48WIIIarzkomIiKgOq1Yh1KJFCyxfvhwnTpzAiRMn0KdPHwwbNkwqdlasWIGgoCCsW7cOcXFxsLKyQv/+/XHnzh3pMWbMmIGwsDCEhoYiOjoad+/exeDBg1FSUiK18fLyQkJCAsLDwxEeHo6EhAR4e3tL50tKSuDp6Yn8/HxER0cjNDQUu3btQkBAgNQmLy8P/fv3h7W1NeLi4rB27VqsXLkSQUFBT/1mERERUd1SrzqNhwwZonV/yZIlWL9+PWJiYuDk5ITVq1dj3rx5GDlyJABgy5YtsLS0xPbt2zFp0iTk5uZi06ZN2Lp1K/r16wcACAkJgY2NDfbt24cBAwYgOTkZ4eHhiImJQffu3QEAGzZsQI8ePXDhwgU4OjoiIiIC586dQ0ZGBqytrQEAgYGB8PHxwZIlS2Bqaopt27bh/v37CA4OhlqthrOzMy5evIigoCD4+/tDpVL94zePiIiIarenHiNUUlKC0NBQ5Ofno0ePHkhNTUVWVhY8PDykNmq1Gr1798bRo0cBAPHx8SguLtZqY21tDWdnZ6nNsWPHoNFopCIIANzc3KDRaLTaODs7S0UQAAwYMACFhYWIj4+X2vTu3RtqtVqrzfXr15GWllbp6yosLEReXp7WjYiIiOqmahdCiYmJaNiwIdRqNd566y2EhYXByckJWVlZAABLS0ut9paWltK5rKwsGBgYwMzMrMo2FhYW5Z7XwsJCq82jz2NmZgYDA4Mq25TdL2tTkWXLlkljkzQaDWxsbKp+Q4iIiKjWqnYh5OjoiISEBMTExODtt9/GuHHjcO7cOen8o5echBCPvQz1aJuK2v8bbcoGSleVZ+7cucjNzZVuGRkZVWYnIiKi2qvahZCBgQEcHBzg6uqKZcuWoVOnTlizZg2srKwAlO9tyc7OlnpirKysUFRUhJycnCrb3Lhxo9zz3rx5U6vNo8+Tk5OD4uLiKttkZ2cDKN9r9TC1Wi3Niiu7ERERUd30j9cREkKgsLAQ9vb2sLKyQmRkpHSuqKgIhw4dQs+ePQEAXbt2Rf369bXaZGZmIikpSWrTo0cP5ObmIjY2Vmpz/Phx5ObmarVJSkpCZmam1CYiIgJqtRpdu3aV2hw+fFhrSn1ERASsra1hZ2f3T182ERER1QHVKoTee+89/P7770hLS0NiYiLmzZuHgwcPYsyYMVCpVJgxYwaWLl2KsLAwJCUlwcfHBw0aNICXlxcAQKPRYMKECQgICEBUVBROnTqFsWPHwsXFRZpF1r59ewwcOBC+vr6IiYlBTEwMfH19MXjwYDg6OgIAPDw84OTkBG9vb5w6dQpRUVGYNWsWfH19pR4cLy8vqNVq+Pj4ICkpCWFhYVi6dClnjBEREZGkWtPnb9y4AW9vb2RmZkKj0aBjx44IDw9H//79AQDvvvsuCgoKMHnyZOTk5KB79+6IiIiAiYmJ9BirVq1CvXr1MGrUKBQUFKBv374IDg6Gvr6+1Gbbtm3w8/OTZpcNHToU69atk87r6+tj7969mDx5Mnr16gUjIyN4eXlh5cqVUhuNRoPIyEhMmTIFrq6uMDMzg7+/P/z9/Z/unSIiIqI6RyW41HKV8vLyoNFokJub+0Tjhezm7H1mWdKWez6Tx2Vmbc8qM/Dscj/LzEREtdGT/v2uVo8QEekeFm9EVJdx01UiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ1WrEFq2bBm6desGExMTWFhYYPjw4bhw4YJWGx8fH6hUKq2bm5ubVpvCwkJMmzYN5ubmMDY2xtChQ3Ht2jWtNjk5OfD29oZGo4FGo4G3tzdu376t1SY9PR1DhgyBsbExzM3N4efnh6KiIq02iYmJ6N27N4yMjNC8eXMsXrwYQojqvGwiIiKqo6pVCB06dAhTpkxBTEwMIiMj8eDBA3h4eCA/P1+r3cCBA5GZmSndfvnlF63zM2bMQFhYGEJDQxEdHY27d+9i8ODBKCkpkdp4eXkhISEB4eHhCA8PR0JCAry9vaXzJSUl8PT0RH5+PqKjoxEaGopdu3YhICBAapOXl4f+/fvD2toacXFxWLt2LVauXImgoKBqvUlERERUN9WrTuPw8HCt+5s3b4aFhQXi4+Px0ksvScfVajWsrKwqfIzc3Fxs2rQJW7duRb9+/QAAISEhsLGxwb59+zBgwAAkJycjPDwcMTEx6N69OwBgw4YN6NGjBy5cuABHR0dERETg3LlzyMjIgLW1NQAgMDAQPj4+WLJkCUxNTbFt2zbcv38fwcHBUKvVcHZ2xsWLFxEUFAR/f3+oVKrqvHwiIiKqY/7RGKHc3FwAQOPGjbWOHzx4EBYWFmjbti18fX2RnZ0tnYuPj0dxcTE8PDykY9bW1nB2dsbRo0cBAMeOHYNGo5GKIABwc3ODRqPRauPs7CwVQQAwYMAAFBYWIj4+XmrTu3dvqNVqrTbXr19HWlpaha+psLAQeXl5WjciIiKqm566EBJCwN/fHy+88AKcnZ2l44MGDcK2bduwf/9+BAYGIi4uDn369EFhYSEAICsrCwYGBjAzM9N6PEtLS2RlZUltLCwsyj2nhYWFVhtLS0ut82ZmZjAwMKiyTdn9sjaPWrZsmTQuSaPRwMbG5onfEyIiIqpdqnVp7GFTp07FmTNnEB0drXV89OjR0n87OzvD1dUVtra22Lt3L0aOHFnp4wkhtC5VVXTZ6t9oUzZQurLLYnPnzoW/v790Py8vj8UQERFRHfVUPULTpk3Dnj17cODAAbRo0aLKts2aNYOtrS0uXboEALCyskJRURFycnK02mVnZ0u9NVZWVrhx40a5x7p586ZWm0d7dXJyclBcXFxlm7LLdI/2FJVRq9UwNTXVuhEREVHdVK1CSAiBqVOnYvfu3di/fz/s7e0f+zO3bt1CRkYGmjVrBgDo2rUr6tevj8jISKlNZmYmkpKS0LNnTwBAjx49kJubi9jYWKnN8ePHkZubq9UmKSkJmZmZUpuIiAio1Wp07dpVanP48GGtKfURERGwtraGnZ1ddV46ERER1UHVKoSmTJmCkJAQbN++HSYmJsjKykJWVhYKCgoAAHfv3sWsWbNw7NgxpKWl4eDBgxgyZAjMzc0xYsQIAIBGo8GECRMQEBCAqKgonDp1CmPHjoWLi4s0i6x9+/YYOHAgfH19ERMTg5iYGPj6+mLw4MFwdHQEAHh4eMDJyQne3t44deoUoqKiMGvWLPj6+kq9OF5eXlCr1fDx8UFSUhLCwsKwdOlSzhgjIiIiANUshNavX4/c3Fy8/PLLaNasmXTbuXMnAEBfXx+JiYkYNmwY2rZti3HjxqFt27Y4duwYTExMpMdZtWoVhg8fjlGjRqFXr15o0KABfvrpJ+jr60tttm3bBhcXF3h4eMDDwwMdO3bE1q1bpfP6+vrYu3cvDA0N0atXL4waNQrDhw/HypUrpTYajQaRkZG4du0aXF1dMXnyZPj7+2uNASIiIiLdVa3B0o9bkdnIyAi//fbbYx/H0NAQa9euxdq1aytt07hxY4SEhFT5OC1btsTPP/9cZRsXFxccPnz4sZmIiIhI93CvMSIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp1VT+4ARET/Nrs5e5/J46Yt93wmj0tE8mGPEBEREeksFkJERESks1gIERERkc6qViG0bNkydOvWDSYmJrCwsMDw4cNx4cIFrTZCCCxcuBDW1tYwMjLCyy+/jLNnz2q1KSwsxLRp02Bubg5jY2MMHToU165d02qTk5MDb29vaDQaaDQaeHt74/bt21pt0tPTMWTIEBgbG8Pc3Bx+fn4oKirSapOYmIjevXvDyMgIzZs3x+LFiyGEqM7LJiIiojqqWoXQoUOHMGXKFMTExCAyMhIPHjyAh4cH8vPzpTYrVqxAUFAQ1q1bh7i4OFhZWaF///64c+eO1GbGjBkICwtDaGgooqOjcffuXQwePBglJSVSGy8vLyQkJCA8PBzh4eFISEiAt7e3dL6kpASenp7Iz89HdHQ0QkNDsWvXLgQEBEht8vLy0L9/f1hbWyMuLg5r167FypUrERQU9FRvFhEREdUt1Zo1Fh4ernV/8+bNsLCwQHx8PF566SUIIbB69WrMmzcPI0eOBABs2bIFlpaW2L59OyZNmoTc3Fxs2rQJW7duRb9+/QAAISEhsLGxwb59+zBgwAAkJycjPDwcMTEx6N69OwBgw4YN6NGjBy5cuABHR0dERETg3LlzyMjIgLW1NQAgMDAQPj4+WLJkCUxNTbFt2zbcv38fwcHBUKvVcHZ2xsWLFxEUFAR/f3+oVKp//AYSERFR7fWPxgjl5uYCABo3bgwASE1NRVZWFjw8PKQ2arUavXv3xtGjRwEA8fHxKC4u1mpjbW0NZ2dnqc2xY8eg0WikIggA3NzcoNFotNo4OztLRRAADBgwAIWFhYiPj5fa9O7dG2q1WqvN9evXkZaWVuFrKiwsRF5entaNiIiI6qanLoSEEPD398cLL7wAZ2dnAEBWVhYAwNLSUqutpaWldC4rKwsGBgYwMzOrso2FhUW557SwsNBq8+jzmJmZwcDAoMo2ZffL2jxq2bJl0rgkjUYDGxubx7wTREREVFs9dSE0depUnDlzBjt27Ch37tFLTkKIx16GerRNRe3/jTZlA6UryzN37lzk5uZKt4yMjCpzExERUe31VIXQtGnTsGfPHhw4cAAtWrSQjltZWQEo39uSnZ0t9cRYWVmhqKgIOTk5Vba5ceNGuee9efOmVptHnycnJwfFxcVVtsnOzgZQvteqjFqthqmpqdaNiIiI6qZqFUJCCEydOhW7d+/G/v37YW9vr3Xe3t4eVlZWiIyMlI4VFRXh0KFD6NmzJwCga9euqF+/vlabzMxMJCUlSW169OiB3NxcxMbGSm2OHz+O3NxcrTZJSUnIzMyU2kRERECtVqNr165Sm8OHD2tNqY+IiIC1tTXs7Oyq89KJiIioDqpWITRlyhSEhIRg+/btMDExQVZWFrKyslBQUADg78tNM2bMwNKlSxEWFoakpCT4+PigQYMG8PLyAgBoNBpMmDABAQEBiIqKwqlTpzB27Fi4uLhIs8jat2+PgQMHwtfXFzExMYiJiYGvry8GDx4MR0dHAICHhwecnJzg7e2NU6dOISoqCrNmzYKvr6/Ui+Pl5QW1Wg0fHx8kJSUhLCwMS5cu5YwxIiIiAlDN6fPr168HALz88staxzdv3gwfHx8AwLvvvouCggJMnjwZOTk56N69OyIiImBiYiK1X7VqFerVq4dRo0ahoKAAffv2RXBwMPT19aU227Ztg5+fnzS7bOjQoVi3bp10Xl9fH3v37sXkyZPRq1cvGBkZwcvLCytXrpTaaDQaREZGYsqUKXB1dYWZmRn8/f3h7+9fnZdNREREdVS1CqEnWZFZpVJh4cKFWLhwYaVtDA0NsXbtWqxdu7bSNo0bN0ZISEiVz9WyZUv8/PPPVbZxcXHB4cOHq2xDREREuol7jREREZHOYiFEREREOouFEBEREeksFkJERESks1gIERERkc5iIUREREQ6i4UQERER6SwWQkRERKSzWAgRERGRzmIhRERERDqLhRARERHprGrtNUZERM+G3Zy9z+Rx05Z7PpPHJaor2CNEREREOouFEBEREeksFkJERESkszhGiIiIngrHNVFdwB4hIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIinVXtQujw4cMYMmQIrK2toVKp8MMPP2id9/HxgUql0rq5ublptSksLMS0adNgbm4OY2NjDB06FNeuXdNqk5OTA29vb2g0Gmg0Gnh7e+P27dtabdLT0zFkyBAYGxvD3Nwcfn5+KCoq0mqTmJiI3r17w8jICM2bN8fixYshhKjuyyYiIqI6qNqFUH5+Pjp16oR169ZV2mbgwIHIzMyUbr/88ovW+RkzZiAsLAyhoaGIjo7G3bt3MXjwYJSUlEhtvLy8kJCQgPDwcISHhyMhIQHe3t7S+ZKSEnh6eiI/Px/R0dEIDQ3Frl27EBAQILXJy8tD//79YW1tjbi4OKxduxYrV65EUFBQdV82ERER1UH1qvsDgwYNwqBBg6pso1arYWVlVeG53NxcbNq0CVu3bkW/fv0AACEhIbCxscG+ffswYMAAJCcnIzw8HDExMejevTsAYMOGDejRowcuXLgAR0dHRERE4Ny5c8jIyIC1tTUAIDAwED4+PliyZAlMTU2xbds23L9/H8HBwVCr1XB2dsbFixcRFBQEf39/qFSq6r58IiIiqkOeyRihgwcPwsLCAm3btoWvry+ys7Olc/Hx8SguLoaHh4d0zNraGs7Ozjh69CgA4NixY9BoNFIRBABubm7QaDRabZydnaUiCAAGDBiAwsJCxMfHS2169+4NtVqt1eb69etIS0urMHthYSHy8vK0bkRERFQ3VbtH6HEGDRqEV199Fba2tkhNTcX8+fPRp08fxMfHQ61WIysrCwYGBjAzM9P6OUtLS2RlZQEAsrKyYGFhUe6xLSwstNpYWlpqnTczM4OBgYFWGzs7u3LPU3bO3t6+3HMsW7YMixYteroXT0REimY3Z+8ze+y05Z7P7LHp2fnXC6HRo0dL/+3s7AxXV1fY2tpi7969GDlyZKU/J4TQulRV0WWrf6NN2UDpyi6LzZ07F/7+/tL9vLw82NjYVJqbiIiIaq9nPn2+WbNmsLW1xaVLlwAAVlZWKCoqQk5Ojla77OxsqbfGysoKN27cKPdYN2/e1GpT1vNTJicnB8XFxVW2KbtM92hvUhm1Wg1TU1OtGxEREdVNz7wQunXrFjIyMtCsWTMAQNeuXVG/fn1ERkZKbTIzM5GUlISePXsCAHr06IHc3FzExsZKbY4fP47c3FytNklJScjMzJTaREREQK1Wo2vXrlKbw4cPa02pj4iIgLW1dblLZkRERKR7ql0I3b17FwkJCUhISAAApKamIiEhAenp6bh79y5mzZqFY8eOIS0tDQcPHsSQIUNgbm6OESNGAAA0Gg0mTJiAgIAAREVF4dSpUxg7dixcXFykWWTt27fHwIED4evri5iYGMTExMDX1xeDBw+Go6MjAMDDwwNOTk7w9vbGqVOnEBUVhVmzZsHX11fqxfHy8oJarYaPjw+SkpIQFhaGpUuXcsYYERERAXiKMUInTpyAu7u7dL9sPM24ceOwfv16JCYm4ptvvsHt27fRrFkzuLu7Y+fOnTAxMZF+ZtWqVahXrx5GjRqFgoIC9O3bF8HBwdDX15fabNu2DX5+ftLssqFDh2qtXaSvr4+9e/di8uTJ6NWrF4yMjODl5YWVK1dKbTQaDSIjIzFlyhS4urrCzMwM/v7+WmOAiIiISHdVuxB6+eWXq1yZ+bfffnvsYxgaGmLt2rVYu3ZtpW0aN26MkJCQKh+nZcuW+Pnnn6ts4+LigsOHDz82ExEREeke7jVGREREOouFEBEREeksFkJERESks1gIERERkc5iIUREREQ6i4UQERER6SwWQkRERKSzWAgRERGRzmIhRERERDqLhRARERHpLBZCREREpLNYCBEREZHOYiFEREREOouFEBEREeksFkJERESks1gIERERkc6qJ3cAIiIiqpzdnL3P7LHTlns+s8euLdgjRERERDqLhRARERHpLBZCREREpLNYCBEREZHOYiFEREREOouFEBEREeksFkJERESks1gIERERkc5iIUREREQ6i4UQERER6SwWQkRERKSzWAgRERGRzmIhRERERDqLu88TERHRv8puzt5n9thpyz3/1cerdo/Q4cOHMWTIEFhbW0OlUuGHH37QOi+EwMKFC2FtbQ0jIyO8/PLLOHv2rFabwsJCTJs2Debm5jA2NsbQoUNx7do1rTY5OTnw9vaGRqOBRqOBt7c3bt++rdUmPT0dQ4YMgbGxMczNzeHn54eioiKtNomJiejduzeMjIzQvHlzLF68GEKI6r5sIiIiqoOqXQjl5+ejU6dOWLduXYXnV6xYgaCgIKxbtw5xcXGwsrJC//79cefOHanNjBkzEBYWhtDQUERHR+Pu3bsYPHgwSkpKpDZeXl5ISEhAeHg4wsPDkZCQAG9vb+l8SUkJPD09kZ+fj+joaISGhmLXrl0ICAiQ2uTl5aF///6wtrZGXFwc1q5di5UrVyIoKKi6L5uIiIjqoGpfGhs0aBAGDRpU4TkhBFavXo158+Zh5MiRAIAtW7bA0tIS27dvx6RJk5Cbm4tNmzZh69at6NevHwAgJCQENjY22LdvHwYMGIDk5GSEh4cjJiYG3bt3BwBs2LABPXr0wIULF+Do6IiIiAicO3cOGRkZsLa2BgAEBgbCx8cHS5YsgampKbZt24b79+8jODgYarUazs7OuHjxIoKCguDv7w+VSvVUbxoRERHVDf/qYOnU1FRkZWXBw8NDOqZWq9G7d28cPXoUABAfH4/i4mKtNtbW1nB2dpbaHDt2DBqNRiqCAMDNzQ0ajUarjbOzs1QEAcCAAQNQWFiI+Ph4qU3v3r2hVqu12ly/fh1paWkVvobCwkLk5eVp3YiIiKhu+lcLoaysLACApaWl1nFLS0vpXFZWFgwMDGBmZlZlGwsLi3KPb2FhodXm0ecxMzODgYFBlW3K7pe1edSyZcukcUkajQY2NjaPf+FERERUKz2T6fOPXnISQjz2MtSjbSpq/2+0KRsoXVmeuXPnIjc3V7plZGRUmZuIiIhqr3+1ELKysgJQvrclOztb6omxsrJCUVERcnJyqmxz48aNco9/8+ZNrTaPPk9OTg6Ki4urbJOdnQ2gfK9VGbVaDVNTU60bERER1U3/aiFkb28PKysrREZGSseKiopw6NAh9OzZEwDQtWtX1K9fX6tNZmYmkpKSpDY9evRAbm4uYmNjpTbHjx9Hbm6uVpukpCRkZmZKbSIiIqBWq9G1a1epzeHDh7Wm1EdERMDa2hp2dnb/5ksnIiKiWqjahdDdu3eRkJCAhIQEAH8PkE5ISEB6ejpUKhVmzJiBpUuXIiwsDElJSfDx8UGDBg3g5eUFANBoNJgwYQICAgIQFRWFU6dOYezYsXBxcZFmkbVv3x4DBw6Er68vYmJiEBMTA19fXwwePBiOjo4AAA8PDzg5OcHb2xunTp1CVFQUZs2aBV9fX6kXx8vLC2q1Gj4+PkhKSkJYWBiWLl3KGWNEREQE4Cmmz584cQLu7u7SfX9/fwDAuHHjEBwcjHfffRcFBQWYPHkycnJy0L17d0RERMDExET6mVWrVqFevXoYNWoUCgoK0LdvXwQHB0NfX19qs23bNvj5+Umzy4YOHaq1dpG+vj727t2LyZMno1evXjAyMoKXlxdWrlwptdFoNIiMjMSUKVPg6uoKMzMz+Pv7S5mJiIhIt1W7EHr55ZerXJlZpVJh4cKFWLhwYaVtDA0NsXbtWqxdu7bSNo0bN0ZISEiVWVq2bImff/65yjYuLi44fPhwlW2IiIhIN3HTVSIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIinfWvF0ILFy6ESqXSullZWUnnhRBYuHAhrK2tYWRkhJdffhlnz57VeozCwkJMmzYN5ubmMDY2xtChQ3Ht2jWtNjk5OfD29oZGo4FGo4G3tzdu376t1SY9PR1DhgyBsbExzM3N4efnh6Kion/7JRMREVEt9Ux6hDp06IDMzEzplpiYKJ1bsWIFgoKCsG7dOsTFxcHKygr9+/fHnTt3pDYzZsxAWFgYQkNDER0djbt372Lw4MEoKSmR2nh5eSEhIQHh4eEIDw9HQkICvL29pfMlJSXw9PREfn4+oqOjERoail27diEgIOBZvGQiIiKqheo9kwetV0+rF6iMEAKrV6/GvHnzMHLkSADAli1bYGlpie3bt2PSpEnIzc3Fpk2bsHXrVvTr1w8AEBISAhsbG+zbtw8DBgxAcnIywsPDERMTg+7duwMANmzYgB49euDChQtwdHREREQEzp07h4yMDFhbWwMAAgMD4ePjgyVLlsDU1PRZvHQiIiKqRZ5Jj9ClS5dgbW0Ne3t7vPbaa7hy5QoAIDU1FVlZWfDw8JDaqtVq9O7dG0ePHgUAxMfHo7i4WKuNtbU1nJ2dpTbHjh2DRqORiiAAcHNzg0aj0Wrj7OwsFUEAMGDAABQWFiI+Pr7S7IWFhcjLy9O6ERERUd30rxdC3bt3xzfffIPffvsNGzZsQFZWFnr27Ilbt24hKysLAGBpaan1M5aWltK5rKwsGBgYwMzMrMo2FhYW5Z7bwsJCq82jz2NmZgYDAwOpTUWWLVsmjTvSaDSwsbGp5jtAREREtcW/XggNGjQI//d//wcXFxf069cPe/fuBfD3JbAyKpVK62eEEOWOPerRNhW1f5o2j5o7dy5yc3OlW0ZGRpW5iIiIqPZ65tPnjY2N4eLigkuXLknjhh7tkcnOzpZ6b6ysrFBUVIScnJwq29y4caPcc928eVOrzaPPk5OTg+Li4nI9RQ9Tq9UwNTXVuhEREVHd9MwLocLCQiQnJ6NZs2awt7eHlZUVIiMjpfNFRUU4dOgQevbsCQDo2rUr6tevr9UmMzMTSUlJUpsePXogNzcXsbGxUpvjx48jNzdXq01SUhIyMzOlNhEREVCr1ejateszfc1ERERUO/zrs8ZmzZqFIUOGoGXLlsjOzsZHH32EvLw8jBs3DiqVCjNmzMDSpUvRpk0btGnTBkuXLkWDBg3g5eUFANBoNJgwYQICAgLQpEkTNG7cGLNmzZIutQFA+/btMXDgQPj6+uLLL78EALz55psYPHgwHB0dAQAeHh5wcnKCt7c3PvnkE/z111+YNWsWfH192ctDREREAJ5BIXTt2jW8/vrr+PPPP9G0aVO4ubkhJiYGtra2AIB3330XBQUFmDx5MnJyctC9e3dERETAxMREeoxVq1ahXr16GDVqFAoKCtC3b18EBwdDX19farNt2zb4+flJs8uGDh2KdevWSef19fWxd+9eTJ48Gb169YKRkRG8vLywcuXKf/slExERUS31rxdCoaGhVZ5XqVRYuHAhFi5cWGkbQ0NDrF27FmvXrq20TePGjRESElLlc7Vs2RI///xzlW2IiIhId3GvMSIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIincVCiIiIiHQWCyEiIiLSWSyEiIiISGexECIiIiKdxUKIiIiIdBYLISIiItJZLISIiIhIZ7EQIiIiIp3FQoiIiIh0FgshIiIi0lkshIiIiEhnsRAiIiIinaUThdDnn38Oe3t7GBoaomvXrvj999/ljkREREQKUOcLoZ07d2LGjBmYN28eTp06hRdffBGDBg1Cenq63NGIiIhIZnW+EAoKCsKECRMwceJEtG/fHqtXr4aNjQ3Wr18vdzQiIiKSWT25AzxLRUVFiI+Px5w5c7SOe3h44OjRoxX+TGFhIQoLC6X7ubm5AIC8vLwnes7SwntPmfbxnjRDdTGztmeVGXh2uZlZGzP/DzNrq42fHcys7Ukzl7UTQlTdUNRhf/zxhwAgjhw5onV8yZIlom3bthX+zIIFCwQA3njjjTfeeOOtDtwyMjKqrBXqdI9QGZVKpXVfCFHuWJm5c+fC399ful9aWoq//voLTZo0qfRnnlZeXh5sbGyQkZEBU1PTf/WxnxVmrhnMXDOYuWYwc81gZm1CCNy5cwfW1tZVtqvThZC5uTn09fWRlZWldTw7OxuWlpYV/oxarYZardY61qhRo2cVEQBgampaa/7RlmHmmsHMNYOZawYz1wxm/h+NRvPYNnV6sLSBgQG6du2KyMhIreORkZHo2bOnTKmIiIhIKep0jxAA+Pv7w9vbG66urujRowe++uorpKen46233pI7GhEREcmszhdCo0ePxq1bt7B48WJkZmbC2dkZv/zyC2xtbeWOBrVajQULFpS7FKdkzFwzmLlmMHPNYOaawcxPRyXE4+aVEREREdVNdXqMEBEREVFVWAgRERGRzmIhRERERDqLhRARERHpLBZCRAqQmpoqd4Rqy8/PlzsCEdE/xkKI6qSUlBS8//77eP3115GdnQ0ACA8Px9mzZ2VOVjEHBwe4u7sjJCQE9+/flzvOE7G0tMT48eMRHR0td5QnlpGRgWvXrkn3Y2NjMWPGDHz11Vcypqqbfv/9d4wdOxY9evTAH3/8AQDYunVrrfr3Qv8+Jf4OshCixyooKMC9e//bSfjq1atYvXo1IiIiZExVuUOHDsHFxQXHjx/H7t27cffuXQDAmTNnsGDBApnTVez06dPo3LkzAgICYGVlhUmTJiE2NlbuWFXasWMHcnNz0bdvX7Rt2xbLly/H9evX5Y5VJS8vLxw4cAAAkJWVhf79+yM2NhbvvfceFi9eLHO6umPXrl0YMGAAjIyMcOrUKRQWFgIA7ty5g6VLl8qcrnpKSkqQkJCAnJwcuaNUqjb1ziryd/Bf2eadnlh6errWTrjHjx8X06dPF19++aWMqarWv39/sX79eiGEEDk5OcLS0lK0aNFCGBoais8//1zmdOW5ubmJwMBAIYQQDRs2FCkpKUIIIWJjY4W1tbWc0R6ruLhY7N69WwwdOlTUr19fODk5icDAQJGdnS13tEr9+eefIigoSHTs2FHUq1dPeHp6il27doni4mK5o5XTqFEjcf78eSGEEGvWrBE9e/YUQgjx22+/CXt7ezmjVSk+Pl6cOXNGuv/DDz+IYcOGiblz54rCwkIZk1XsueeeE1u2bBFCaP8Onjp1SlhaWsoZ7bGmT58uNm7cKIQQ4sGDB6JXr15CpVIJY2NjceDAAXnDVcLY2Fi88cYb4vfff5c7ymMp8XeQhVANe+GFF8Q333wjhBAiMzNTmJqaih49eogmTZqIRYsWyZyuYk2aNBFJSUlCCCE2bNggOnbsKEpKSsS3334r2rVrJ3O68oyNjcWVK1eEENofwqmpqUKtVssZ7Yndv39fBAUFCbVaLVQqlTAwMBDe3t7i+vXrcker0qeffiplbtq0qZg/f77Iz8+XO5bE2NhYpKamCiGEGDJkiFi+fLkQQoirV68KQ0NDGZNVzdXVVXz//fdCCCFSUlKEoaGheP3114WDg4OYPn26vOEqYGRkJL3PD/8OpqSkKP53sHnz5iIuLk4IIURYWJiwtrYWFy5cEPPmzZP+aCvNnj17xMiRI4WBgYFo06aNWLZsmfjjjz/kjlUhJf4O8tJYDUtKSsLzzz8PAPj222/h7OyMo0ePYvv27QgODpY3XCXu3bsHExMTAEBERARGjhwJPT09uLm54erVqzKnK69Ro0bIzMwsd/zUqVNo3ry5DIme3IkTJzB58mQ0a9YMQUFBmDVrFlJSUrB//3788ccfGDZsmNwRy8nKysKKFSvQvn17zJkzB//5z38QFRWFVatWISwsDMOHD5c7oqRDhw744osv8PvvvyMyMhIDBw4EAFy/fh1NmjSROV3lLl68iOeeew4A8N133+Gll16SPjN27dolb7gKNGvWDJcvXy53PDo6Gq1atZIh0ZP7888/YWVlBQD45Zdf8Oqrr6Jt27aYMGECEhMTZU5XsSFDhmDXrl24fv063n77bezYsQO2trYYPHgwdu/ejQcPHsgdUaLI30FZyi8dpsRq+HFcXFzEmjVrRHp6ujA1NRVHjx4VQghx4sQJRXZzv/POO+KFF14QmZmZwsTERFy6dElER0eLVq1aiYULF8odr0KBgYHC2dlZ1K9fXwwbNkz89NNPoqSkRKvNpUuXhL6+vkwJy9u1a5cYPHiwqF+/vujUqZNYu3atyMnJ0WqTlJQk6tevL0/AChw4cEA0atRI6OnpiTfeeEM6PnfuXDFixAgZk1XNxMREXLx4UQghRL9+/cTq1auFEMr93Pj444+Fk5OTiImJESYmJuL3338XISEhomnTpmLt2rVyx6tSy5YtxW+//SYePHggbGxsxE8//SSE+PvfcqNGjWRO9+SU2jurxN9BFkI17PnnnxezZ88Whw8fFoaGhiIhIUEIIcSxY8dE8+bNZU5Xse+++07Ur19f6Onpif79+0vHly5dKgYOHChjsooVFRUJLy8voaenJ1QqlZR97Nix4sGDB3LHq5CDg4NYunSpyMzMrLRNYWGhCA4OrsFUVTM1NRWTJk0SsbGxlba5d++e4orPBw8eiL/++kvrWGpqqrhx44ZMiR7P3d1d/Pe//xXffPONqF+/vrh06ZIQQoiDBw8KW1tbecNV4r333hNGRkZCpVIJlUolDA0Nxfvvvy93rMdasGCB0Gg0ol27dqJly5bi/v37QgghNm3aJNzc3GROV7XMzEzx8ccfi3bt2okGDRqIMWPGiP3794uQkBDh7Oys9fktJ6X9DnLT1Rp28OBBjBgxAnl5eRg3bhy+/vprAMB7772H8+fPY/fu3TInrFhWVhYyMzPRqVMn6On9fUU1NjYWpqamaNeunczp/kcIgfT0dDRt2hRZWVk4efIkSktL0blzZ7Rp00bueHXGgwcP8NVXX2HkyJHSZYTa4sGDBzh48CBSUlLg5eUFExMTXL9+HaampmjYsKHc8Sp05swZjBkzBunp6fD395dmP06bNg23bt3C9u3bZU5YsXv37uHcuXMoLS2Fk5OTYt/fR33//ffIyMjAq6++ihYtWgAAtmzZgkaNGiny8vTu3buxefNm/Pbbb3BycsLEiRMxduxYNGrUSGpz9uxZdO7cGUVFRfIF/f+U9jvIQkgGJSUlyMvLg5mZmXQsLS0NDRo0gIWFhYzJar/S0lIYGhri7NmztarwOXPmTIXHVSoVDA0N0bJlS6jV6hpOVbUGDRogOTkZtra2ckd5YlevXsXAgQORnp6OwsJCXLx4Ea1atcKMGTNw//59fPHFF3JHrJb79+9DX18f9evXlzuKlvHjx2PNmjXS2MIy+fn5mDZtmvQFkP4dGo0Gr732GiZOnIhu3bpV2KagoAArVqyQfQkRJf4OshCiCo0cOfKJ2yqtF6tDhw7YtGkT3Nzc5I7yxPT09KBSqSo9X79+fYwePRpffvklDA0NazBZ5dzd3TF9+nRFDYZ+nOHDh8PExASbNm1CkyZNcPr0abRq1QqHDh3CxIkTcenSJbkjVur27dv4/vvvkZKSgnfeeQeNGzfGyZMnYWlpqbhJAPr6+sjMzCz3xa5sILKSBu8CwKeffvrEbf38/J5hkqdz7949NGjQQO4YT0SJv4P1avwZdVDnzp2r/CP3sJMnTz7jNE9Go9HIHeGprVixAu+88w7Wr18PZ2dnueM8kbCwMMyePRvvvPMOnn/+eQghEBcXh8DAQCxYsAAPHjzAnDlz8P7772PlypVyxwUATJ48GQEBAbh27Rq6du0KY2NjrfMdO3aUKVnloqOjceTIERgYGGgdt7W1lVY/VqIzZ86gb9++aNSoEdLS0uDr64vGjRsjLCwMV69exTfffCN3RABAXl4exN9jT3Hnzh2tor2kpAS//PKLInu9V61a9UTtVCqVIguhBw8eIC8vr9xxlUoFtVpd7t+7nJT4O8hCqAbUpm/MZTZv3ix3hKc2duxY3Lt3D506dYKBgQGMjIy0zv/1118yJavckiVLsGbNGgwYMEA61rFjR7Ro0QLz589HbGwsjI2NERAQoJhCaPTo0QC0vyGrVCoIIaBSqVBSUiJXtEqVlpZWmOvatWvlLuMoib+/P9544w2sWLFCK+egQYPg5eUlYzJtjRo1gkqlgkqlQtu2bcudV6lUWLRokQzJqlYb9/p7WNn7XpkWLVrAx8cHCxYskMZ4ykWJv4MshGqA3Ndkdc3q1avljlBtiYmJFY61sbW1ldYuee655ypcH0kutfGPR//+/bF69WppXyOVSoW7d+9iwYIFeOWVV2ROV7m4uDh8+eWX5Y43b94cWVlZMiSq2IEDByCEQJ8+fbBr1y40btxYOmdgYABbW1tYW1vLmLBuCg4Oxrx58+Dj46PVo7xlyxa8//77uHnzJlauXAm1Wo333ntP1qxK/B3kGCF6It9//z2+/fZbpKenl5t1oJTLebVZ586d0alTJ3z11VdSl3FxcTF8fX1x+vRpnDp1CkeOHMHYsWNrZQGiFNevX4e7uzv09fVx6dIluLq64tKlSzA3N8fhw4cVedkG+HuD2/DwcHTu3BkmJibSuIqIiAhMmDABGRkZckfUcvXqVdjY2Mje+/C0rl27hj179lT4eRcUFCRTqsr17dsXkyZNwqhRo7SOf/vtt/jyyy8RFRWFrVu3YsmSJTh//rxMKf+mxN9BFkI1rKSkBKtWraq0qFDiZZtPP/0U8+bNw7hx47Bhwwa88cYbSElJQVxcHKZMmYIlS5bIHbFSBQUFKC4u1jpmamoqU5rKHT16FEOHDoWenh46duwIlUqFM2fOoKSkBD///DPc3NywdetWZGVl4Z133pE7rpZz585V+G956NChMiWqWkFBAXbs2CEtrdClSxeMGTOm3CVUJXnzzTdx8+ZNfPvtt2jcuDHOnDkDfX19DB8+HC+99JJie0Hv3btX4b8NJY4fKxMVFYWhQ4fC3t4eFy5cgLOzM9LS0iCEQJcuXbB//365I5bToEEDnD59utxM2UuXLqFTp064d+8eUlNT0aFDB60NtOVSUFCA0NBQxMfHK+N3sKYXLtJ18+fPF82aNROffPKJMDQ0FB9++KGYMGGCaNKkiVizZo3c8Srk6Ogotm/fLoTQ3jdo/vz5YsqUKXJGq9Ddu3fFlClTRNOmTYWenl65m1LduXNHrF+/XsycOVPMmDFDfPHFFyIvL0/uWJVKSUkRHTt2FCqVSlq8suy/lfw+10a5ubmiV69eolGjRkJfX1/Y2NiI+vXri5deekncvXtX7njlZGdnC09Pzwp//5T+b6Nbt25i/vz5Qoj/fd7duXNHDB06VJGbTAshRJs2bcTs2bPLHZ89e7Zo27atEEKIuLg4xW86LRf2CNWw1q1b49NPP4WnpydMTEyQkJAgHYuJiVHkwmgPrxdjYWGByMhIdOrUCZcuXYKbmxtu3bold0QtU6ZMwYEDB7B48WL897//xWeffYY//vgDX375JZYvX44xY8bIHbFOGDJkCPT19bFhwwa0atUKsbGxuHXrljSg+8UXX5Q7IgBgz549T9xWqb1YZfbv36/Vk9WvXz+5I1VozJgxSEtLw+rVq+Hu7o6wsDDcuHEDH330EQIDA+Hp6Sl3xEo9/LlsZmaG6OhodOjQAadPn8awYcOQlpYmd8Ry9uzZg1dffRXt2rVDt27doFKpEBcXh/Pnz+P777/H4MGDsX79ely6dEn2S3vLli2DpaUlxo8fr3X866+/xs2bNzF79uyaDyV3JaZrGjRoIK5evSqEEMLKykrEx8cLIf7+dm1qaipntErZ29tLOV1dXcUXX3whhBDit99+E2ZmZnJGq5CNjY04cOCAEEJIe40JIcQ333wjBg0aJGOyql2+fFlMnTpV9O3bV/Tr10/4+fmJy5cvyx2rUk2aNBGnT58WQvy93cb58+eFEEJERUWJ5557Ts5oWsp6qh53U3pPRW1iZWUljh8/LoT4+3fwwoULQgghfvzxR9GrVy85oz2WpaWlOHv2rBBCCCcnJ/Hjjz8KIYRISEgQxsbGckarUlpampgzZ44YMWKEGD58uJgzZ460r6WS2NraiiNHjpQ7HhMTI+zs7GRIJARnjdWwFi1aIDMzEy1btoSDgwMiIiLQpUsXxMXFKW7l4DJ9+vTBTz/9hC5dumDChAmYOXMmvv/+e5w4caJaCy/WlL/++gv29vYA/h4PVDbu6oUXXsDbb78tZ7RK/fbbbxg6dCiee+459OrVC0IIHD16FF9++SV++ukn9O/fX+6I5ZSUlEjL4Zubm+P69etwdHSEra0tLly4IHO6/yktLZU7wlP59NNP8eabb8LQ0PCxC/4pbW2b/Px8adBr48aNcfPmTbRt2xYuLi6Kn1zh5uaGI0eOwMnJCZ6enggICEBiYiJ2796tyEVai4uL4eHhgS+//BLLli2TO85jZWVloVmzZuWON23aVLZZsSyEatiIESMQFRWF7t27Y/r06Xj99dexadMmpKenY+bMmXLHq9BXX30l/TF566230LhxY0RHR2PIkCF46623ZE5XXqtWrZCWlgZbW1s4OTnh22+/xfPPP4+ffvpJa+8dJZkzZw5mzpyJ5cuXlzs+e/ZsRRZCzs7OOHPmDFq1aoXu3btjxYoVMDAwwFdffYVWrVrJHa/WW7VqFcaMGQNDQ8MqF/xT4iJ/jo6OuHDhAuzs7PDcc8/hyy+/hJ2dHb744osK/wgqSVBQEO7evQsAWLhwIe7evYudO3fCwcHhiRderEn169dHUlLSEy/aKzcbGxscOXJE+rJa5siRI/ItrSBLPxRJjh07JgIDA6XuV/rngoKCpIHn+/fvF0ZGRsLAwEDo6emJ1atXy5yuYmq1Wly8eLHc8QsXLgi1Wi1DoscLDw8Xu3btEkL8fWm3ffv2QqVSCXNzcxEVFSVzusrt27dPeHp6ilatWonWrVsLT09PERkZKXesOiUkJERs3rxZCCHEyZMnpYkLhoaGIjQ0VN5wdZC/v3+Fg6WVaPny5aJJkybi66+/FmlpaSItLU1s2rRJNGnSRCxdulSWTBwsTRU6c+YMnJ2doaenV+mGoGWUPBUWANLT03HixAm0bt0anTp1kjtOhWxsbBAUFIRXX31V6/i3336LWbNmIT09XaZk1fPXX3/BzMxMsd9O161bh5kzZ+I///kPevToAQCIiYnB999/j6CgIEydOlXmhBVbvHgxZs2aVW4/qYKCAnzyySf44IMPZEr2ZO7du4fz58+jZcuWMDc3lztOnTNt2jR88803cHBwgKura7ntbuQeIP0wIQTmzJmDTz/9VFpWwdDQELNnz5bt3zELoRqwZ88eDBo0CPXr13/sDBalzFrR09NDVlYWLCwspA1BK/qnotStFGqbxYsXY9WqVZgzZw569uwJlUqF6OhofPzxxwgICMD7778vd8Q6oXnz5pg7d265guezzz7DkiVLcP36dZmSVa2yTUxv3boFCwsLxf0O1rbCrXHjxrh48SLMzc0fW8grca03d3f3Ss+pVCpFrn109+5dJCcnw8jICG3atJF1jCwLoRrwaFFRGSUVFVevXkXLli2hUqlw9erVKttWtDWEHPbv34+pU6ciJiam3KKJubm56NmzJ7744gvFTOt+mBACq1evRmBgoPTH2NraGu+88w78/PwU2cOSn5+P5cuXIyoqCtnZ2eUGJV+5ckWmZJUzMTHBqVOn4ODgoHX80qVL6Ny5szQ2RGn09PRw48YNNG3aVOv4/v37MXr0aNy8eVOmZBWrbYXbli1b8Nprr0GtVmPLli1Vth03blwNpaKawsHSNeDhPxC1ZQbLw8WNUgqdx1m9ejV8fX0rXDlao9Fg0qRJCAoKUmQhpFKpMHPmTMycORN37twBAEVvAgoAEydOxKFDh+Dt7Y1mzZopslh71NChQxEWFlZude4ff/wRQ4YMkSlV5cp6J8o2MX34PS4pKcHdu3cVOWFB/P+Ndx91+vRprf3HlKKsuHnw4AEAYMCAAbCyspIz0lO5fPkyUlJS8NJLL8HIyKjS/w81beTIkQgODoapqeljZxrv3r27hlL9DwuhGvTwNMeKdmZWKkUugFWB06dP4+OPP670vIeHh2J2bq+K0gugMr/++iv27t2LXr16yR3libVv3x5LlizBwYMHtcYIHTlyBAEBAVrT1JUwE2v16tUQQmD8+PFYtGgRNBqNdM7AwAB2dnbS61CC2lq4lalXrx7efvttJCcnyx2lWm7duoVRo0bhwIEDUKlUuHTpElq1aoWJEyeiUaNGCAwMlDWfRqOR/i08/G9YKXhprIY1bdoUR48eLbcnjJLZ2dlh+/bt6Nmzp9bx48eP47XXXlPMJqCGhoZISkoqd9mjzOXLl+Hi4oKCgoIaTlaxzp07P/G3NSWuvWJvb49ffvkF7du3lzvKE3t0ym5lVCqVoi7tHTp0CD179kT9+vXljlKlLVu2SIXb6tWrFV+4VcTd3R3Tp0/H8OHD5Y7yxP773/8iOzsbGzduRPv27bU25Z05cybOnj0rd0RFY49QDfvvf/+LTZs2lVsvRsmUuABWRZo3b47ExMRKC6EzZ84oag2T2vRBW5EPP/wQH3zwAbZs2VJuUKxSKaVofxJ5eXnSZd7OnTujoKCg0iJeKRsJl11isre3R69evVCvXu37EzN58mQEBATg2rVr6Nq1a7kZWEqcJRsREYHffvsNLVq00Drepk2bx47xrGmLFi3C2LFj0bp1a7mjSGrfv9JarqioCBs3bkRkZKTipzmWUeQCWBV45ZVX8MEHH2DQoEEwNDTUOldQUIAFCxZg8ODBMqUrb8GCBXJH+EcCAwORkpICS0tL2NnZleutUGIvVm1iZmYmDThu1KhRhb2HZWNAlDb42MTEBMnJyXBxcQHw9xiszZs3w8nJCQsXLoSBgYHMCSs3evRoANqXRstmzSrxvQb+nrhQ0ZeRP//8U3E7FuzatQuLFy9Gt27dMHbsWIwePbrcJICaxkKohiUlJaFLly4AgIsXL8qc5slMnDgRM2bMQHFxMfr06QMAiIqKwrvvvouAgACZ0/3P+++/j927d6Nt27aYOnUqHB0doVKpkJycjM8++wwlJSWYN2+e3DGrFB8fj+TkZKhUKjg5OaFz585yR6pUbe3RunbtGvbs2YP09HRpHZMySvoisn//fmlg8YEDB2ROUz2TJk3CnDlz4OLigitXrmD06NEYOXIkvvvuO9y7dw+rV6+WO2KlalOvYZmXXnoJ33zzDT788EMAfxdupaWl+OSTT6qcWi+HM2fO4OzZs9i2bRuCgoLg7++Pfv36YezYsRg+fLg8vcs1voQj1TqlpaXi3XffFYaGhkJPT0/o6emJBg0aiEWLFskdrZy0tDQxaNAgoaenp7WZ5qBBgxS5AWGZGzduCHd3d6FSqYSZmZlo1KiRUKlUok+fPiI7O1vueHXGvn37RIMGDUSHDh1EvXr1xHPPPScaNWokNBqNcHd3lztenWFqaiptGLx8+XLh4eEhhBAiOjpatGjRQs5oddLZs2dF06ZNxcCBA4WBgYH4z3/+I9q3by8sLS0VvXGzEH//m5g8ebJo2rSpMDExkSUDB0vXsPHjx2PNmjXlZgbl5+dj2rRp+Prrr2VK9nhKWgDrcXJycnD58mUIIdCmTRuYmZnJHalKo0ePRkpKCrZu3SoNPj537hzGjRsHBwcH7NixQ+aElatNvVjPP/88Bg4ciMWLF8PExASnT5+GhYUFxowZg4EDBypqU97Hrej+MKWNWzE1NUV8fDzatGmD/v37Y/DgwZg+fTrS09Ph6OiomAkLldm6dSu++OILpKam4tixY7C1tcXq1athb2+PYcOGyR2vQllZWVi/fj3i4+NRWlqKLl26YMqUKYoaF1mRhIQEhISEIDQ0FLdu3ZLn34Ys5ZcO09PTEzdu3Ch3/ObNm0JfX1+GRKQEpqamIjY2ttzx48ePC41GU/OBnkBt7MVq2LCh9A25UaNGIikpSQghREJCgrC1tZUxWXllvZllPZuV3fT09OSOWo67u7v473//K7755htRv359cenSJSGEEAcPHlTc+/yozz//XJibm4uPPvpIGBkZiZSUFCGEEJs3bxYvv/yyzOnqhitXroiPPvpItG/fXujr6wt3d3exYcMGcfv2bVnycIxQDcnLy4MQAkII3LlzR2swb0lJCX755Zdyq7AqRW1cQbi2KS0trXBqdP369RW7COe0adOQl5eHs2fPluvF8vPzU2QvlrGxMQoLCwH8vXJ3SkoKOnToAODvgaVKUhvHqpRZvXo1xowZgx9++AHz5s2TZnJ+//335ZbhUJq1a9diw4YNGD58uNbsXldXV8yaNUvGZFW7ffs2YmNjK/yM/u9//ytTqvJ69OiB2NhYuLi44I033oCXlxeaN28uayYWQjWkbNZH2UJjj1KpVFi0aJEMyR6vNq4gXNv06dMH06dPx44dO6SZeH/88QdmzpyJvn37ypyuYuHh4di3b5/WOkJOTk747LPP4OHhIWOyyrm5ueHIkSNwcnKCp6cnAgICkJiYiN27d8PNzU3ueFpqy4ruFenYsSMSExPLHf/kk0+gr68vQ6Inl5qaWuHlXbVajfz8fBkSPd5PP/2EMWPGID8/HyYmJlqf0SqVSlGFkLu7OzZu3Ch9AVECFkI15MCBAxBCoE+fPti1a5fWMvMGBgawtbVV1FT0h9XGFYRrm3Xr1mHYsGGws7ODjY0NVCoV0tPT4eLigpCQELnjVag29mIFBQVJ+4ktXLgQd+/exc6dO+Hg4IBVq1bJnE5bbdysOTY2Fl27dpWKHfHIFg8qlQphYWEYNWqUXBEfy97eHgkJCeUK0V9//RVOTk4ypapaQEAAxo8fj6VLlyp6Ta/i4mKEhoZi7NixckfRwsHSNezhzUxri9q4gnBtFRkZifPnz0MIAScnJ/Tr10/uSJUaNmwYbt++Xa4Xa8yYMTAzM0NYWJjMCWu32rhZ86ObrZqamiIhIQGtWrUCANy4cQPW1taKyVuRzZs3Y/78+QgMDMSECROwceNGpKSkYNmyZdi4cSNee+01uSOWY2xsjMTEROl9VrLmzZuX60mWGwuhGhYeHo6GDRvihRdeAAB89tln2LBhg3RJQYmzm0JCQvDjjz/WqhWEL168iIMHD1Z4vfyDDz6QKVXdkpGRgWHDhiEpKalcL9aPP/5YbpVbJWjVqhXi4uLQpEkTreO3b99Gly5dON7tH3q4eAMgzcx7uBBq1qyZYnsMy2zYsAEfffQRMjIyAPz9x3vhwoWYMGGCzMkqNnLkSLz22muK7mkrs3z5cpw/fx4bN25UzMrjLIRqmIuLCz7++GO88sorSExMhKurKwICArB//360b98emzdvljtiOZ07d0ZKSgqEELViBeENGzbg7bffhrm5OaysrMp1zSstb5moqKhKB6QreVmF2tSL9egf6jI3btxAy5YtpYHUSvPNN99g9OjR5ZasKCoqQmhoqGLGgDxJIaT0HqGH/fnnnygtLVXsRJYymzZtwuLFi/HGG2/AxcWl3Ge0Ui6dAsCIESMQFRWFhg0bwsXFpdzuCnLsPs9CqIY1bNgQSUlJsLOzw8KFC5GUlITvv/8eJ0+exCuvvIKsrCy5I5bzuEHcStsqwtbWFpMnT8bs2bPljvLEFi1ahMWLF8PV1bXCAem8zPTPlI2xGT58OLZs2aK1GWhJSQmioqIQGRmJCxcuyBWxSo9ecipz69YtWFhYKKawqAuFUJ8+fbB79240atRI63heXh6GDx+O/fv3yxOsCrXl0ikAvPHGG1Wel6MzQBn9UjrEwMAA9+7dAwDs27dP+ibXuHFj5OXlyRmtUkordB4nJycHr776qtwxquWLL75AcHAwvL295Y5SpU8//RRvvvkmDA0N8emnn1bZ9uG9muRWth2ISqWSNgYtU79+fdjZ2SEwMFCGZE/m0UHHZa5du6ZV1CnBuXPnpC90QgicP39eGqCutCUKKnLw4MFyW68AwP379/H777/LkOjxlH6p8WFKvOrBQqiGvfDCC/D390evXr0QGxuLnTt3Avh7TIsSx1TURq+++ioiIiLw1ltvyR3liRUVFSl+fRUAWLVqFcaMGQNDQ8MqZ1mpVCpFFUJlfyjs7e0RFxcHc3NzmRM9mc6dO0vLbvTt21drTEVJSQlSU1MxcOBAGROW17dvXzx8oaFso+OHNy5VoodX8n64mAP+fq/Dw8NlX+/mUa+88gp27NghFcNLlizBlClTpN6sW7du4cUXX8S5c+dkTFnegwcPcPDgQaSkpMDLywsmJia4fv06TE1N0bBhwxrPw0tjNSw9PR2TJ09GRkYG/Pz8pMF3M2fORElJyWO/ZcuhpKQEq1atwrffflvhRpV//fWXTMn+5+H3LT8/H0FBQfD09KzwermS/kCXmT17Nho2bIj58+fLHYUUZNGiRRBCYPHixQgICND6I2FgYAA7Ozv83//9n2J2c7969eoTtVPiGkl6enpSkVbRn0UjIyOsXbsW48ePr+lolaqNs/SuXr2KgQMHIj09HYWFhbh48SJatWqFGTNm4P79+/jiiy9qPBMLIXqsDz74ABs3boS/vz/mz5+PefPmIS0tDT/88AM++OADRRQW9vb2T9ROpVIpcmbQ9OnT8c0336Bjx47o2LFjueJNSbuil1m8eDFmzZpVbiZhQUEBPvnkE0XNzjt+/Dj++usvDBo0SDr2zTffYMGCBcjPz8fw4cOxdu1axe6fV9lgafr3XL16FUIItGrVCrGxsWjatKl0zsDAABYWFopbDLI2jskaPnw4TExMsGnTJjRp0kTKe+jQIUycOBGXLl2q8UwshGpYenp6ledbtmxZQ0meXOvWrfHpp5/C09MTJiYmSEhIkI7FxMRg+/btckes9dzd3Ss9p1KpFDlAs7YM4AWAQYMG4eWXX5YG0CcmJqJLly7w8fFB+/bt8cknn2DSpElYuHChvEEf8XAvxcNMTU3h6OiId999FyNHjpQhGSlBbSyEzM3NceTIETg6OmrlTUtLg5OTkzSGtiZxjFANs7Ozq/IauZL+wZbJysqCi4sLgL9nveXm5gL4+9q/Ei/l1KaeijIHDhyQO0K1VTbe4/Tp01orpytBQkICPvzwQ+l+aGgounfvjg0bNgAAbGxssGDBAsUVQrt3767wPS7bV2rs2LHYsmVLrZscUBucO3euwqEASpqKXjZ+7NFjSlZaWlrh37lr167BxMREhkQshGrcqVOntO4XFxfj1KlTCAoKwpIlS2RKVbUWLVogMzMTLVu2hIODAyIiItClSxfExcUpsqt+0aJFeOutt8oVQvfu3cOiRYsUWQjVJmZmZlr75j38wVtSUoK7d+8qbqB6Tk4OLC0tpfuHDh3SGmTcrVs3afE8JSmb7VaRcePGwcnJCStXrmQh9C+6cuUKRowYgcTERGmAN/C/AkNJX1aFEPDx8ZE+h+/fv4+33npLWptHieti9e/fH6tXr8ZXX30F4O/39e7du1iwYAFeeeUVWTKxEKphnTp1KnfM1dUV1tbW+OSTTxTZzV22AFb37t0xffp0vP7669i0aRPS09Mxc+ZMueOVU5t6Ksrk5+dj+fLllS6oqKRxTatXr4YQAuPHj8eiRYu0pm+XDeDt0aOHjAnLs7S0RGpqKmxsbFBUVISTJ09qrY91586dCvdNUzoPDw+8//77cseoU6ZPnw57e3vs27dPGi9069YtBAQEYOXKlXLH0/LoUhAV7eGllMU2y6xatQru7u5wcnLC/fv34eXlhUuXLsHc3Bw7duyQJRMLIYVo27Yt4uLi5I5RoeXLl0v//Z///ActWrTA0aNH4eDgoKhu4trYU1Fm4sSJOHToELy9vStcUFFJyj587e3t0atXL8Usk1+VgQMHYs6cOfj444/xww8/oEGDBnjxxRel82fOnEHr1q1lTPh0CgoKYGhoKHeMOuXYsWPYv38/mjZtCj09Pejp6eGFF17AsmXL4OfnV65XX05KXJPncaytrZGQkIDQ0FDEx8ejtLQUEyZMwJgxY2BkZCRLJg6WrmGPLpoohEBmZiYWLlyI8+fPIyEhQZ5gdcCWLVuknorVq1fXip6KMo0aNcLevXvRq1cvuaNUS0pKCjZv3oyUlBSsWbMGFhYWCA8Ph42NDTp06CB3PMnNmzcxcuRIHDlyBA0bNsSWLVswYsQI6Xzfvn3h5uam2MvTlZk2bRpSUlLwyy+/yB1FWvPoSSh1mxvg7y9U8fHxaNWqFVq3bo2NGzfC3d0dKSkpcHFxkWUwLz1byv8qV8c0atSo3IeFEAI2NjYIDQ2VKdXj1YZNTB/uqejZs2etutRhZmam2Mt2lTl06BAGDRqEXr164fDhw1iyZAksLCxw5swZbNy4Ed9//73cESVNmzbF77//jtzcXDRs2LDcNOjvvvtOloXcHsff37/C47m5uThx4gRSUlIUs9pxVeOZahNnZ2ecOXMGrVq1Qvfu3bFixQoYGBjgq6++qhW7uyvV5cuXkZubi65du0rHoqKi8NFHH0lLWLz33nuyZGOPUA07dOiQ1n09PT00bdoUDg4Oir3EUBs2Ma3O9iSmpqbPMMnTCQkJwY8//ogtW7aUG+StVD169MCrr74Kf39/rWmwcXFxGD58OP744w+5I9Z6lS2rYGpqinbt2mHy5MmKXJywNvvtt9+Qn5+PkSNH4sqVKxg8eDDOnz+PJk2aIDQ0FH379pU7Yq00YsQIODs7S7M3U1NT0aFDB7z44oto164dvv76a3z44YeYMWNGjWdjIUSPVRs2Ma1svZWHlQ2iVsqsj0cvJVy+fBlCCNjZ2ZXrzVJCsfmohg0bIjExEfb29uXWA2nXrh3u378vd0Sif8Vff/0ljUGkp2NjY4Nvv/1WGp7w0Ucf4fvvv5eGg2zatAlr166VZXiIMrsg6piyna+fhJIGH5epDZuY1sZ1eGr7pYRGjRohMzOz3Krep06dUtyeTFSzasO2PI960q0zvv7662ecpG76888/tfbTPHDgAIYMGSLdf/nllxEQECBHNBZCNeHRP3gPr01Rdr+MUnorHlYbNjHt3bu33BGqbcGCBXJH+Ee8vLwwe/ZsfPfdd1CpVCgtLcWRI0cwa9YsxU3ZpZq1aNGiKrflUaLg4GDY2tqic+fOFe41Rv9M48aNkZmZCRsbG5SWluLEiRNay68UFRXJ9r6zEKoBDw8u3rdvH2bPno2lS5eiR48eUKlUOHr0KN5//30sXbpUxpSVc3BwwPz58xETE1NrNjEF/l5AsaJvox07dpQpUeXi4uJQWlqK7t27ax0/fvw49PX14erqKlOyyi1ZsgQ+Pj5o3rw5hBBwcnJCSUkJvLy8FLm2TXFxMd58803Mnz+fg16fsW3btmHDhg3w9PTEokWL8Prrr6N169bo2LEjYmJiFPmZ8dZbbyE0NBRXrlzB+PHjMXbs2Fo3gUHJevfujQ8//BCff/45vvvuO5SWlmqNgTt37hzs7OzkCSeoRnXo0EH8/vvv5Y4fPnxYtGvXToZEj2dnZ1fpzd7eXu545WRnZwtPT0+hp6dX4U2JunXrJr777rtyx3ft2iWef/55GRJVrbS0VKSlpYn8/HyRkpIivvvuO7Fz505x8eJFuaNVSaPRiJSUFLlj1HkNGjQQV69eFUIIYWVlJeLj44UQQqSkpAhTU1M5o1Xp/v37Yvv27aJfv36iQYMG4tVXXxXh4eGitLRU7mi13pUrV0Tr1q2Fnp6eqFevnvj888+1zg8bNkzMmDFDlmzsEaphKSkpWuvblNFoNEhLS6v5QE8gNTVV7gjVMmPGDOTk5CAmJgbu7u4ICwvDjRs38NFHHyEwMFDueBU6d+4cunTpUu54586dce7cORkSVU0IgTZt2uDs2bNo06ZNrelhGTFiBH744YdKp6XTv6O2bctTRq1W4/XXX8frr7+Oq1evIjg4GJMnT0ZxcTHOnTunyCUWagt7e3skJyfj3LlzaNq0KaytrbXOL1q0SGsMUU1iIVTDunXrhhkzZiAkJATNmjUD8PempgEBAXj++edlTlc37N+/Hz/++CO6desGPT092Nraon///jA1NcWyZcvg6ekpd8Ry1Go1bty4Ua6gyMzMVOSyCnp6emjTpg1u3bqFNm3ayB3niTk4OODDDz/E0aNH0bVrV2lPpjJKvGRTG9W2bXkqUrZKvRCi3Npp9HTq169f4TZTQMXbT9UUTp+vYZcvX8aIESNw4cIFtGzZEgCQnp6Otm3b4ocffoCDg4PMCf/m7++PDz/8EMbGxo/99hwUFFRDqZ6Mqakpzpw5Azs7O9jZ2WHbtm3o1auXtG6FEleGfe2115CVlYUff/xR6jG8ffs2hg8fDgsLC3z77bcyJyxv7969WL58OdavXw9nZ2e54zyRR2e4PUylUilqT7e6JCYmRpHb8jyqsLAQu3fvxtdff43o6GgMHjwYb7zxBgYOHAg9PT2549EzoryvmnWcg4MDzpw5g8jISJw/f14aZNqvXz9FrVFx6tQpnD9/Hp07d65ybx0lZS7j6OiICxcuwM7ODs899xy+/PJL2NnZ4YsvvpB64ZQmMDAQL730kjRrBQASEhJgaWmJrVu3ypyuYmPHjsW9e/fQqVMnGBgYlNsnSIlTpGvbZd66ws3NDW5ubnLHqNLkyZMRGhqKli1b4o033kBoaCiaNGkidyyqAewRokrp6+sjMzMTFhYWAIDRo0fj008/haWlpczJqrZt2zYUFxfDx8cHp06dwoABA3Dr1i0YGBggODgYo0ePljtihfLz87Ft2zacPn0aRkZG6NixI15//XXFbhWyZcuWKs8/ujO2khQVFSE1NRWtW7dW5KXHumDr1q344osvkJqaimPHjsHW1harV6+Gvb09hg0bJne8cvT09NCyZcvH7pm2e/fuGkxFNYGFkAyioqIQFRVV4b5dSlqsS09PD1lZWVIhZGpqioSEhFozMLbMvXv3cP78ebRs2RLm5uZyxyEZ3bt3D9OmTZOKuIsXL6JVq1bw8/ODtbU15syZI3PCumH9+vX44IMPMGPGDCxZsgRJSUlo1aoVgoODsWXLFkUugOrj4/NEPdy1ccd3qhq/CtWwRYsWYfHixXB1dUWzZs0UeWmpMrWtZn74W39FM7KUZuvWrfjyyy9x5coV6Rv0qlWr0KpVK0V+g/7ll1+gr6+PAQMGaB2PiIhASUkJBg0aJFOyys2dOxenT5/GwYMHMXDgQOl4v379sGDBAhZC/5K1a9diw4YNGD58OJYvXy4dd3V1xaxZs2RMVrng4GC5I+iM27dvIzY2tsLOAFkWY5Vl0r4Os7KyEt98843cMZ6Inp6eyM7Olu43bNhQXLlyRcZETyY/P1+MHz9e6OvrC319fWndmGnTpolly5bJnK5in3/+uTA3NxcfffSRMDQ0lDJv3rxZvPzyyzKnq5iLi4vYu3dvueO//vqr6NixowyJHq9ly5bi2LFjQoi//z2Xvc+XLl0SJiYmckarUwwNDUVaWpoQQvt9vnjxojA0NJQzGslsz549wsTEROjp6QmNRiMaNWok3czMzGTJxGHwNayoqAg9e/aUO8YTEULAx8cHI0eOxMiRI3H//n289dZb0v2ym9I8/K3f0NBQOt6vXz/s3LlTxmSVK/sGPW/ePK0xK66urkhMTJQxWeUuXboEJyencsfbtWuHy5cvy5Do8W7evCld6n1Yfn5+reqdVTp7e/sKN8/89ddfK/w3Q7ojICAA48ePx507d3D79m3k5ORIN7kmWPDSWA2bOHEitm/fjvnz58sd5bEeHew6duxYmZJUzw8//ICdO3fCzc1N64+bk5MTUlJSZExWudTUVGm22MPUajXy8/NlSPR4Go0GV65cKbcs/uXLl8utz6MU3bp1w969ezFt2jQA/5v1uGHDBmlXbPrn3nnnHUyZMgX379+HEAKxsbHYsWMHli1bho0bN8odj2T0xx9/wM/PDw0aNJA7ioSFUA27f/8+vvrqK+zbtw8dO3YsNyNISWvy1NZBgbXxW3/ZN2hbW1ut40r+Bj106FDMmDEDYWFhaN26NYC/i6CAgADFrhWzbNkyDBw4EOfOncODBw+wZs0anD17FseOHcOhQ4fkjldnvPHGG3jw4AHeffdd3Lt3D15eXmjevDnWrFmD1157Te54JKMBAwbgxIkTipp0w0Kohp05cwbPPfccACApKUneMHVUbfrWv3jxYsyaNatWfoP+5JNPMHDgQLRr105aGv/atWt48cUXsXLlSpnTVaxnz544cuQIVq5cidatW0tbPxw7dgwuLi5yx6tTfH194evriz///BOlpaXSl5M//vgDzZs3lzkdycXT0xPvvPMOzp07V+Em3nJ8ieL0eapzjh49ioEDB2LMmDEIDg7GpEmTtL71d+3aVe6IkofXatqwYQM++ugjZGRkAACaN2+OhQsXYsKECTKnrJwQApGRkVprH7300ktyxyIFysrKwpIlS7Bx40YUFBTIHYdkUtUK3SqVCiUlJTWY5v8/LwuhmvEkg4pVKhV27dpVA2nqvsTERKxcuRLx8fEoLS1Fly5dMHv2bMV96390rSYA5b5B1ya3b99Go0aN5I7xWNnZ2RVO3e3YsaNMieqG27dvY8qUKYiIiED9+vUxZ84cTJ06FQsXLsTKlSvRoUMH+Pv74/XXX5c7KpGEl8ZqSEU7ztOz4+Li8tiVj5Xi0XFLtWXRx48//hh2dnbSSt2jRo3Crl27YGVlhV9++UXWTRQrEx8fj3HjxiE5ObnculhyfRutS9577z0cPnwY48aNQ3h4OGbOnInw8HDcv38fv/76K3r37i13RKJy2CNEdUZeXt4TtTM1NX3GSZ6cnp4enJ2dH7vNw8mTJ2so0ZNr1aoVQkJC0LNnT0RGRmLUqFHYuXMnvv32W6SnpyMiIkLuiOV07NgRDg4OmD17NiwtLcsVoY8OVqfqsbW1xaZNm9CvXz9cuXIFDg4O8PPzw+rVq+WORgpy6NAhrFy5EsnJyVCpVGjfvj3eeecdvPjii7LkYY8Q1RmNGjWqclaYEEKR3/oHDBiAhg0byh2j2jIzM2FjYwMA+PnnnzFq1Ch4eHjAzs4O3bt3lzldxVJTU7F79244ODjIHaVOun79ujTLsVWrVjA0NMTEiRNlTkVKEhISgjfeeAMjR46En58fhBA4evQo+vbti+DgYHh5edV4JhZCVGc8vH+REAKvvPIKNm7cqPgZKu+8806tHA9kZmaGjIwM2NjYIDw8HB999BGAv997pRWbZfr27YvTp0+zEHpGSktLtWYB6evrK3ZNKZLHkiVLsGLFCsycOVM6Nn36dAQFBeHDDz+UpRDipTGqs0xMTHD69GlFrVfxqIdnjdU2U6dOxc8//4w2bdrg1KlTSEtLQ8OGDbFz5058/PHHiryc9+eff2LcuHF4/vnn4ezsrIipu3WJnp4eBg0aBLVaDQD46aef0KdPn3LFEHdw111qtRpnz54t92Xk8uXLcHZ2xv3792s8E3uEiGRUm7+HrFq1CnZ2dsjIyMCKFSuky3uZmZmYPHmyzOkqdvToUURHR+PXX38td06Jl01rm9q6Gj3VHBsbG0RFRZUrhKKioqRL7TWNPUJUZ9WGHqGrV6+iZcuWil3xuq6xs7PD4MGDMX/+fFhaWsodh0jnrF+/HjNmzMD48ePRs2dPqFQqREdHIzg4GGvWrMGkSZNqPBMLIaqzTExMcObMGdjb28sdpc7Ys2cPBg0ahPr162PPnj1VtlXiZSYTExMkJCRIW4IQUc0LCwtDYGAgkpOTAUCaNTZs2DBZ8rAQojrj0UUrOT7h3/fwApBKXCH2ccaNG4cXX3yRM5mISMIxQlRnPLpoJccn/PseXon50VWZa4O2bdti7ty5iI6OrnCfIz8/P5mSEZFc2CNERDqjqsukKpUKV65cqcE0RLqhcePGuHjxIszNzWFmZlblmMi//vqrBpP9jT1CRApx+/ZtxMbGVrgH1n//+1+ZUlWstLQUwcHB2L17N9LS0qBSqWBvb4///Oc/8Pb2Vuzg79TUVLkjEOmcVatWwcTERPpvpX0+sEeISAF++uknjBkzBvn5+TAxMdH6oFCpVLJ8S6qMEAJDhgyR9hNr164dhBBITk5GYmIihg4dih9++EHumERET4SFEJECtG3bFq+88gqWLl2KBg0ayB2nSps3b8b06dPx448/wt3dXevc/v37MXz4cKxbt05xvVgAMH78+CrPf/311zWUhEg3VbaI7K1bt2BhYSHLJAteGiNSgD/++AN+fn6KL4IAYMeOHXjvvffKFUEA0KdPH8yZMwfbtm1TZCGUk5Ojdb+4uBhJSUm4ffs2+vTpI1MqIt1RWd9LYWEhDAwMajjN31gIESnAgAEDcOLECUUv/ljmzJkzWLFiRaXnBw0ahE8//bQGEz25sLCwcsdKS0sxefLkWvHeE9VWZZ8JKpUKGzdu1NpouqSkBIcPH0a7du1kycZLY0QKsGnTJixevBhvvPFGhdO6lbQ4oYGBAa5evYpmzZpVeP769euwt7dHYWFhDSd7ehcuXMDLL7+MzMxMuaMQ1UllMzavXr2KFi1aQF9fXzpnYGAAOzs7LF68GN27d6/xbCyEiBSgNi1OqK+vj6ysLDRt2rTC8zdu3IC1tbWiMj/OL7/8gnHjxuHmzZtyRyGq09zd3bF7926YmZnJHUXCS2NEClCbFicUQsDHx0faYfxRSu4J8vf317ovhEBmZib27t1bbsNQIvr3HThwQO4I5bBHiIiq5Y033niidps3b37GSarv0QHeenp6aNq0Kfr06YPx48ejXj1+NyR61q5du4Y9e/YgPT0dRUVFWueCgoJqPA8LISKFOHToEFauXInk5GSoVCppI8IXX3xR7mhERP+KqKgoDB06FPb29rhw4QKcnZ2RlpYGIQS6dOmC/fv313imygcmEFGNCQkJQb9+/dCgQQP4+flh6tSpMDIyQt++fbF9+3a549UZBQUFuHfvnnT/6tWrWL16NSIiImRMRaQ75s6di4CAACQlJcHQ0BC7du1CRkYGevfujVdffVWWTOwRIlKA9u3b480338TMmTO1jgcFBWHDhg1ITk6WKVnd4uHhgZEjR+Ktt97C7du34ejoCAMDA/z5558ICgrC22+/LXdEojrNxMQECQkJaN26NczMzBAdHY0OHTrg9OnTGDZsGNLS0mo8E3uEiBTgypUrGDJkSLnjQ4cO5f5Y/6KTJ09Klxq///57WFlZ4erVq/jmm28Uu/YRUV1ibGwsTaiwtrZGSkqKdO7PP/+UJRNHBhIpgI2NDaKiouDg4KB1PCoqCjY2NjKlqnvu3bsnbf4YERGBkSNHQk9PD25ubrh69arM6YjqPjc3Nxw5cgROTk7w9PREQEAAEhMTsXv3bri5ucmSiYUQkQIEBATAz88PCQkJ6NmzJ1QqFaKjoxEcHIw1a9bIHa+c4uJivPnmm5g/f36tWpHZwcEBP/zwA0aMGIHffvtNuhSZnZ0NU1NTmdMR1X1BQUG4e/cuAGDhwoW4e/cudu7cCQcHB6xatUqWTBwjRKQQYWFhCAwMlMYDlc0aGzZsmMzJKtaoUSOcPHmyVhVC33//Pby8vFBSUoK+fftKg6SXLVuGw4cP49dff5U5IRHVNBZCRPRUyrYDeXSRQqXLyspCZmYmOnXqJK3oHRsbC1NTU9n2OiLSFXFxcSgtLS23lcbx48ehr68PV1fXGs/ES2NE9FQcHBzw4Ycf4ujRo+jatSuMjY21zvv5+cmUrGpWVlawsrLSOvb888/LlIZIt0yZMgXvvvtuuULojz/+wMcff4zjx4/XeCb2CBHJpHHjxrh48SLMzc1hZmYGlUpVadu//vqrBpM9mbJNFCuiUqlw5cqVGkzzZPLz87F8+XJERUUhOzu73NYmSsxMVJc0bNgQZ86cKXdJPTU1FR07dsSdO3dqPBN7hIhksmrVKmkG06pVq6oshJSoNk7rnzhxIg4dOgRvb280a9as1r3nRLWdWq3GjRs3yhVCmZmZsm1xwx4hIvpHioqKkJqaitatWyt+r65GjRph79696NWrl9xRiHTSa6+9hqysLPz444/QaDQAgNu3b2P48OGwsLDAt99+W+OZuKAikQLo6+sjOzu73PFbt25BX19fhkSPd+/ePUyYMAENGjRAhw4dkJ6eDuDvsUHLly+XOV3FzMzM0LhxY7ljEOmswMBAZGRkwNbWFu7u7nB3d4e9vT2ysrIQGBgoSyYWQkQKUFnHbGFhIQwMDGo4zZOZO3cuTp8+jYMHD8LQ0FA63q9fP+zcuVPGZJX78MMP8cEHH2jtN0ZENad58+Y4c+YMVqxYAScnJ3Tt2hVr1qxBYmKibIvHKrsfm6iOK9vWQaVSYePGjWjYsKF0rqSkBIcPH1bslO4ffvgBO3fuhJubm9ZYGycnJ61l85UkMDAQKSkpsLS0hJ2dHerXr691/uTJkzIlI9IdxsbGePPNN+WOIWEhRCSjspVUhRD44osvtC6DGRgYwM7ODl988YVc8ap08+ZNWFhYlDuen5+v2EHIw4cPlzsCkc7Zs2cPBg0ahPr162PPnj1Vth06dGgNpfofDpYmUgB3d3fs3r0bZmZmckd5Yr1798Z//vMfTJs2DSYmJjhz5gzs7e0xdepUXL58GeHh4XJHJCIF0NPTQ1ZWFiwsLKRFTCuiUqlQUlJSg8n+xh4hIgU4cOCA3BGqbdmyZRg4cCDOnTuHBw8eYM2aNTh79iyOHTuGQ4cOyR2vSvHx8UhOToZKpYKTkxM6d+4sdySiOuvh9boeXbtLCdgjRKQQ165dw549e5Ceno6ioiKtc0FBQTKlqlpiYiJWrlyJ+Ph4lJaWokuXLpg9ezZcXFzkjlah7OxsvPbaazh48CAaNWoEIQRyc3Ph7u6O0NBQNG3aVO6IRFTDWAgRKUBUVBSGDh0Ke3t7XLhwAc7OzkhLS4MQAl26dMH+/fvljlgnjB49GikpKdi6dSvat28PADh37hzGjRsHBwcH7NixQ+aERHVfVFRUpau7f/311zWeh4UQkQI8//zzGDhwIBYvXgwTExOcPn0aFhYWGDNmDAYOHIi3335b7oiVys7OrvADrWPHjjIlqpxGo8G+ffvQrVs3reOxsbHw8PDA7du35QlGpCMWLVqExYsXw9XVtcLV3cPCwmo8E8cIESlAcnKy1BtRr149FBQUoGHDhli8eDGGDRumyEIoPj4e48aNQ3Jycrl1kOQa9Pg4paWl5abMA0D9+vUVOXaBqK754osvEBwcDG9vb7mjSLigIpECGBsbo7CwEABgbW2ttQ7Pn3/+KVesKr3xxhto27Ytjh49iitXriA1NVW6KXXz0j59+mD69Om4fv26dOyPP/7AzJkz0bdvXxmTEemGoqIi9OzZU+4YWtgjRKQAbm5uOHLkCJycnODp6YmAgAAkJiZi9+7dcHNzkztehVJTU7F79244ODjIHeWJrVu3DsOGDYOdnR1sbGygUqmQnp4OFxcXhISEyB2PqM6bOHEitm/fjvnz58sdRcJCiEgBgoKCcPfuXQDAwoULcffuXezcuRMODg7SootK07dvX5w+fbpWFUI2NjY4efIkIiMjcf78eQgh4OTkhH79+skdjUgn3L9/H1999RX27duHjh07lrtULccMWQ6WJqKn8ueff2LcuHF4/vnn4ezsXO4DTY4VYolI2dzd3Ss9p1KpZJkhy0KISGHu3r1bbuCuqampTGkqt2fPHnh7e+POnTvlziltsPT+/fsxdepUxMTElHsvc3Nz0bNnT3zxxRd48cUXZUpIRHLhYGkiBUhNTYWnpyeMjY2h0WhgZmYGMzMzNGrUSLHbbvj5+cHb2xuZmZkoLS3VuimpCAKA1atXw9fXt8KCUqPRYNKkSYpdtJKIni32CBEpQNksiunTp8PS0rLc2hq9e/eWI1aVTExMkJCQgNatW8sd5bFsbW0RHh4uLaL4qPPnz8PDwwPp6ek1nIxIt7i7u1e5KbMcl8Y4WJpIAc6cOYP4+Hg4OjrKHeWJjRw5EgcOHKgVhdCNGzcqXD+oTL169XDz5s0aTESkm5577jmt+8XFxUhISEBSUhLGjRsnSyYWQkQK0K1bN2RkZNSqQqht27aYO3cuoqOj4eLiUq7Q8PPzkylZec2bN0diYmKlM9zOnDmDZs2a1XAqIt1T2SzYstmycuClMSIFSElJwVtvvYWxY8dWOANLidtV2NvbV3pOpVIpalHFadOm4eDBg4iLi4OhoaHWuYKCAjz//PNwd3fHp59+KlNCIt12+fJlPP/88/jrr79q/LlZCBEpQExMDLy8vJCWliYdU6lUEEIobgZWbXTjxg106dIF+vr6mDp1KhwdHaFSqZCcnIzPPvsMJSUlOHnyJCwtLeWOSqSTtm7ditmzZ2ut+l5TeGmMSAHGjx+Pzp07Y8eOHRUOlqZ/xtLSEkePHsXbb7+NuXPnSnujqVQqDBgwAJ9//jmLIKIaMHLkSK37QghkZmbixIkTsq02zR4hIgUwNjaudas0jx8/vsrzX3/9dQ0lqZ6cnBxcvnwZQgi0adNGscsTENVFb7zxhtZ9PT09NG3aFH369IGHh4csmdgjRKQAffr0qXWFUE5Ojtb94uJiJCUl4fbt2+jTp49MqR7PzMwM3bp1kzsGkU7avHmz3BHKYSFEpABDhgzBzJkzkZiYWOEMLCVuVxEWFlbuWGlpKSZPnoxWrVrJkIiIahOlrKLPS2NECqCnV/ki77VtsPSFCxfw8ssvIzMzU+4oRKQwqampmDp1Kg4ePIj79+9Lx+WcGMIeISIFePRbUW2WkpKCBw8eyB2DiBRozJgxAP4eQ6iUiSEshIhk9uDBAxgaGiIhIQHOzs5yx3li/v7+WvfLZn/s3btXthViiUjZlLiKPgshIpnVq1cPtra2teryFwCcOnVK637Z7I/AwMDHzigjIt2kxFX0OUaISAE2b96M7777DiEhIWjcuLHccYiIngklrqLPQohIATp37ozLly+juLgYtra2MDY21jp/8uRJmZJVrqCgAEIINGjQAABw9epVhIWFwcnJSbb1QIhI2ZS4ij4vjREpwPDhw+WOUG3Dhg3DyJEj8dZbb+H27dt4/vnnYWBggD///BNBQUF4++235Y5IRAqjxFX02SNERE/F3Nwchw4dQocOHbBx40asXbsWp06dwq5du/DBBx8gOTlZ7ohEpDBKXEWfPUJEChIfH4/k5GSoVCo4OTmhc+fOckeq1L1792BiYgIAiIiIwMiRI6Gnpwc3NzdcvXpV5nREpERKXEWfhRCRAmRnZ+O1117DwYMH0ahRIwghkJubC3d3d4SGhqJp06ZyRyzHwcEBP/zwA0aMGIHffvsNM2fOBPD3a5FjdVgiUj4lrqLPS2NECjB69GikpKRg69ataN++PQDg3LlzGDduHBwcHLBjxw6ZE5b3/fffw8vLCyUlJejbty8iIiIAAMuWLcPhw4fx66+/ypyQiJRGiavosxAiUgCNRoN9+/aV2ww0NjYWHh4euH37tjzBHiMrKwuZmZno1KmT9AEXGxsLU1NTtGvXTuZ0RESPx0tjRApQWlparosYAOrXr6/o7TesrKxgZWWldez555+XKQ0RUfWxR4hIAYYNG4bbt29jx44dsLa2BgD88ccfGDNmDMzMzCrc6V1u+fn5WL58OaKiopCdnV2uYLty5YpMyYhIyWJjY3Hw4MEKPzeCgoJqPA97hIgUYN26dRg2bBjs7OxgY2MDlUqF9PR0uLi4ICQkRO54FZo4cSIOHToEb29vNGvWTBHrgRCRsi1duhTvv/8+HB0dy60jJNdnCHuEiBQkMjIS58+fhxACTk5O6Nevn9yRKtWoUSPs3bsXvXr1kjsKEdUSlpaW+Pjjj+Hj4yN3FAl7hIhk0rhxY1y8eBHm5uYYP3481qxZg/79+6N///5yR3siZmZm3BeNiKpFT09PcV+eKp/HRkTPVFFREfLy8gAAW7Zswf3792VOVD0ffvghPvjgA9y7d0/uKERUS8ycOROfffaZ3DG08NIYkUz69++PGzduoGvXrtiyZQtGjx4NIyOjCtt+/fXXNZzu8Tp37oyUlBQIIWBnZ1du1psSN4olInmVlpbC09MTFy9ehJOTU7nPjd27d9d4Jl4aI5JJSEgIVq1ahZSUFKhUKuTm5taqXqHauFEsEclr2rRpOHDgANzd3dGkSRNFTLJgjxCRAtjb2+PEiRNo0qSJ3FGIiJ4ZExMThIaGwtPTU+4oEvYIESlAamqq3BGeWm3aKJaI5NW4cWO0bt1a7hha2CNEpBBRUVGVLk6oxDFCtXGjWCKS1+bNmxEeHo7NmzejQYMGcscBwEKISBEWLVqExYsXw9XVtcLFCZW4snRt3CiWiOSlxEkWLISIFKBZs2ZYsWIFvL295Y7yxGrrRrFEJJ9FixZVeX7BggU1lOR/OEaISAGKiorQs2dPuWNUS23dKJaI5CNHofM47BEiUoDZs2ejYcOGmD9/vtxRnlht3CiWiJRBSZMs2CNEpAD379/HV199hX379qFjx47lelrk2JH5cWrjRrFEJC8lTrJgjxCRAri7u1d6TqVSYf/+/TWYpnpq00axRCQvJU6yYCFERERENUKJkyy46SoRVcv+/fvh5OQkbRj7sNzcXHTo0AG///67DMmISOmUOMmCPUJEMho5cuQTtZNjI8LKDB06FO7u7pg5c2aF5z/99FMcOHCAg6WJqBwlTrJgjxCRjDQazRPdlOT06dMYOHBgpec9PDwQHx9fg4mIqLZYt24d7ty5Azs7O7Ru3RoODg6wt7fHnTt3sHbtWlkysUeIiKrF0NAQSUlJcHBwqPD85cuX4eLigoKCghpORkS1hZImWXD6PBFVS/PmzZGYmFhpIXTmzBk0a9ashlMRUW3Sv39/9O/fX+4YAHhpjIiq6ZVXXsEHH3yA+/fvlztXUFCABQsWYPDgwTIkIyKlUvIkC14aI6JquXHjBrp06QJ9fX1MnToVjo6OUKlUSE5OxmeffYaSkhKcPHkSlpaWckclIoVQ8iQLFkJEVG1Xr17F22+/jd9++w1lHyEqlQoDBgzA559/Djs7O3kDEpGi2NraIjw8XFpE8VHnz5+Hh4cH0tPTazgZxwgR0VOwtbXFL7/8gpycHFy+fBlCCLRp0wZmZmZyRyMiBbpx40aF6weVqVevHm7evFmDiR56blmelYjqBDMzs3IrxBIRPUrJkyw4WJqIiIieKSVPsuAYISIiInqmlDzJgoUQERERPXNKnWTBQoiIiIhqjNImWbAQIiIiIp3FwdJERESks1gIERERkc5iIUREREQ6i4UQERER6SwWQkREABYuXIjnnntO7hhEVMNYCBER/YuKi4vljkBE1cBCiIhqle+//x4uLi4wMjJCkyZN0K9fP+Tn5wMANm/ejPbt28PQ0BDt2rXD559/rvWz165dw2uvvYbGjRvD2NgYrq6uOH78OIKDg7Fo0SKcPn0aKpUKKpUKwcHBAID09HQMGzYMDRs2hKmpKUaNGoUbN25Ij1nWk/T111+jVatWUKvV4KokRLUHN10lolojMzMTr7/+OlasWIERI0bgzp07+P333yGEwIYNG7BgwQKsW7cOnTt3xqlTp+Dr6wtjY2OMGzcOd+/eRe/evdG8eXPs2bMHVlZWOHnyJEpLSzF69GgkJSUhPDwc+/btAwBoNBoIITB8+HAYGxvj0KFDePDgASZPnozRo0fj4MGDUq7Lly/j22+/xa5du6Cvry/Tu0NET4OFEBHVGpmZmXjw4AFGjhwJW1tbAICLiwsA4MMPP0RgYCBGjhwJALC3t8e5c+fw5ZdfYty4cdi+fTtu3ryJuLg4NG7cGAC0dsJu2LAh6tWrBysrK+lYZGQkzpw5g9TUVNjY2AAAtm7dig4dOiAuLg7dunUDABQVFWHr1q1o2rTps38TiOhfxUKIiGqNTp06oW/fvnBxccGAAQPg4eGB//znP3jw4AEyMjIwYcIE+Pr6Su0fPHgAjUYDAEhISEDnzp2lIuhJJCcnw8bGRiqCAMDJyQmNGjVCcnKyVAjZ2tqyCCKqpVgIEVGtoa+vj8jISBw9ehQRERFYu3Yt5s2bh59++gkAsGHDBnTv3r3czwCAkZFRtZ9PCAGVSvXY48bGxtV+bCJSBg6WJqJaRaVSoVevXli0aBFOnToFAwMDHDlyBM2bN8eVK1fg4OCgdbO3twcAdOzYEQkJCfjrr78qfFwDAwOUlJRoHXNyckJ6ejoyMjKkY+fOnUNubi7at2//7F4kEdUY9ggRUa1x/PhxREVFwcPDAxYWFjh+/Dhu3ryJ9u3bY+HChfDz84OpqSkGDRqEwsJCnDhxAjk5OfD398frr7+OpUuXYvjw4Vi2bBmaNWuGU6dOwdraGj169ICdnR1SU1ORkJCAFi1awMTEBP369UPHjh0xZswYrF69Whos3bt3b7i6usr9dhDRv4A9QkRUa5iamuLw4cN45ZVX0LZtW7z//vsIDAzEoEGDMHHiRGzcuBHBwcFwcXFB7969ERwcLPUIGRgYICIiAhYWFnjllVfg4uKC5cv/Xzt3bMIwEINhVDeCCy9wgxgOXLj3UtnkcHcbJl0mCKT43xtB1YcEen1PZ/d913VdNcaofd9rzlmttVpr1bZtdRxHnedZvfd6nuefYwB+qL09vAAAQtkIAQCxhBAAEEsIAQCxhBAAEEsIAQCxhBAAEEsIAQCxhBAAEEsIAQCxhBAAEEsIAQCxhBAAEOsDEwhEDZDDDrAAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df['sector'].value_counts().plot(kind = 'bar')"
    ]
@@ -132,9 +757,427 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>OneHotEncoder()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "OneHotEncoder()"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from sklearn.preprocessing import OneHotEncoder\n",
     "onehot = OneHotEncoder()\n",
@@ -143,9 +1186,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "sector_enc = onehot.transform(df[['sector']])\n",
     "sector_enc.toarray()"
@@ -168,7 +1228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -181,9 +1241,433 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;onehot&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)),\n",
+       "                (&#x27;knn&#x27;,\n",
+       "                 DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;onehot&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)),\n",
+       "                (&#x27;knn&#x27;,\n",
+       "                 DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3)</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('onehot', OneHotEncoder(handle_unknown='ignore')),\n",
+       "                ('knn',\n",
+       "                 DecisionTreeClassifier(criterion='entropy', max_depth=3))])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "pipe1 = Pipeline(\n",
     "    [\n",
@@ -197,9 +1681,433 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-4 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-4 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-4 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-4 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;onehot&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)),\n",
+       "                (&#x27;knn&#x27;,\n",
+       "                 DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;onehot&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)),\n",
+       "                (&#x27;knn&#x27;,\n",
+       "                 DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=3)</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('onehot', OneHotEncoder(handle_unknown='ignore')),\n",
+       "                ('knn',\n",
+       "                 DecisionTreeClassifier(criterion='entropy', max_depth=3))])"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "X0 = df[['sector']]\n",
     "Y0 = df['target']\n",
@@ -210,7 +2118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -220,7 +2128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -230,9 +2138,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'accuracy_score_train': 0.5119228438717438,\n",
+       " 'accuracy_score_test': 0.5113911787691189,\n",
+       " 'cohen_kappa_train': 0.0,\n",
+       " 'cohen_kappa_test': 0.0,\n",
+       " 'log_loss_train': 0.6928461137803972,\n",
+       " 'log_loss_test': 0.6928758971552175,\n",
+       " 'f1_score_train': 0.6771811748816596,\n",
+       " 'f1_score_test': 0.676715844253633}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "res = {\n",
     "    'accuracy_score_train': accuracy_score(Y0_train, Y_pred_train),\n",
@@ -267,7 +2193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -276,7 +2202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -297,7 +2223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -386,7 +2312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -411,7 +2337,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -426,9 +2352,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'log_loss_train': 0.692293492470195,\n",
+       " 'log_loss_test': 0.6924102214658684,\n",
+       " 'cohen_kappa_train': 0.018568204793696252,\n",
+       " 'cohen_kappa_test': 0.015454437406455135,\n",
+       " 'f1_score_train': 0.6257843468213725,\n",
+       " 'f1_score_test': 0.6244894693264126,\n",
+       " 'accuracy_score_train': 0.5159395236712562,\n",
+       " 'accuracy_score_test': 0.5140881528066014}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Evaluate hyperparameter configuration 2\n",
     "pipe_d3 = pipe.set_params(**{'decisiontree__max_depth': 3})\n",
@@ -438,9 +2382,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'log_loss_train': 0.6887529288669105,\n",
+       " 'log_loss_test': 0.7544098738491859,\n",
+       " 'cohen_kappa_train': 0.027547393862800473,\n",
+       " 'cohen_kappa_test': 0.014243731538251203,\n",
+       " 'f1_score_train': 0.6478284801018614,\n",
+       " 'f1_score_test': 0.642686248924363,\n",
+       " 'accuracy_score_train': 0.5218705615691253,\n",
+       " 'accuracy_score_test': 0.514923223056042}"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Evaluate hyperparameter configuration 2\n",
     "pipe_d15 = pipe.set_params(**{'decisiontree__max_depth':15})\n",
@@ -497,7 +2459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -515,18 +2477,366 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>fit_time</th>\n",
+       "      <th>score_time</th>\n",
+       "      <th>test_accuracy</th>\n",
+       "      <th>train_accuracy</th>\n",
+       "      <th>test_f1</th>\n",
+       "      <th>train_f1</th>\n",
+       "      <th>test_precision</th>\n",
+       "      <th>train_precision</th>\n",
+       "      <th>test_recall</th>\n",
+       "      <th>train_recall</th>\n",
+       "      <th>test_roc_auc</th>\n",
+       "      <th>train_roc_auc</th>\n",
+       "      <th>test_neg_log_loss</th>\n",
+       "      <th>train_neg_log_loss</th>\n",
+       "      <th>test_neg_brier_score</th>\n",
+       "      <th>train_neg_brier_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>20.323882</td>\n",
+       "      <td>1.062443</td>\n",
+       "      <td>0.514164</td>\n",
+       "      <td>0.520387</td>\n",
+       "      <td>0.633265</td>\n",
+       "      <td>0.642973</td>\n",
+       "      <td>0.515979</td>\n",
+       "      <td>0.519364</td>\n",
+       "      <td>0.819556</td>\n",
+       "      <td>0.843800</td>\n",
+       "      <td>0.513194</td>\n",
+       "      <td>0.524244</td>\n",
+       "      <td>-0.757911</td>\n",
+       "      <td>-0.689198</td>\n",
+       "      <td>-0.250998</td>\n",
+       "      <td>-0.248362</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>21.894017</td>\n",
+       "      <td>1.103001</td>\n",
+       "      <td>0.514236</td>\n",
+       "      <td>0.521126</td>\n",
+       "      <td>0.633761</td>\n",
+       "      <td>0.638298</td>\n",
+       "      <td>0.515992</td>\n",
+       "      <td>0.520282</td>\n",
+       "      <td>0.821185</td>\n",
+       "      <td>0.825562</td>\n",
+       "      <td>0.512013</td>\n",
+       "      <td>0.525087</td>\n",
+       "      <td>-0.826486</td>\n",
+       "      <td>-0.689107</td>\n",
+       "      <td>-0.251993</td>\n",
+       "      <td>-0.248325</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>22.849393</td>\n",
+       "      <td>1.074077</td>\n",
+       "      <td>0.514883</td>\n",
+       "      <td>0.521407</td>\n",
+       "      <td>0.641219</td>\n",
+       "      <td>0.644272</td>\n",
+       "      <td>0.515886</td>\n",
+       "      <td>0.519928</td>\n",
+       "      <td>0.846992</td>\n",
+       "      <td>0.846784</td>\n",
+       "      <td>0.510649</td>\n",
+       "      <td>0.525496</td>\n",
+       "      <td>-0.853786</td>\n",
+       "      <td>-0.688600</td>\n",
+       "      <td>-0.252847</td>\n",
+       "      <td>-0.248141</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>21.055260</td>\n",
+       "      <td>1.036505</td>\n",
+       "      <td>0.514507</td>\n",
+       "      <td>0.521414</td>\n",
+       "      <td>0.638745</td>\n",
+       "      <td>0.642847</td>\n",
+       "      <td>0.515818</td>\n",
+       "      <td>0.520062</td>\n",
+       "      <td>0.838594</td>\n",
+       "      <td>0.841528</td>\n",
+       "      <td>0.513798</td>\n",
+       "      <td>0.525427</td>\n",
+       "      <td>-0.735036</td>\n",
+       "      <td>-0.689149</td>\n",
+       "      <td>-0.250659</td>\n",
+       "      <td>-0.248321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-0.620605</td>\n",
+       "      <td>1.067572</td>\n",
+       "      <td>0.513769</td>\n",
+       "      <td>0.521541</td>\n",
+       "      <td>0.631610</td>\n",
+       "      <td>0.641667</td>\n",
+       "      <td>0.515832</td>\n",
+       "      <td>0.520255</td>\n",
+       "      <td>0.814402</td>\n",
+       "      <td>0.836996</td>\n",
+       "      <td>0.512235</td>\n",
+       "      <td>0.525106</td>\n",
+       "      <td>-0.769125</td>\n",
+       "      <td>-0.689139</td>\n",
+       "      <td>-0.251287</td>\n",
+       "      <td>-0.248325</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    fit_time  score_time  test_accuracy  train_accuracy   test_f1  train_f1  \\\n",
+       "0  20.323882    1.062443       0.514164        0.520387  0.633265  0.642973   \n",
+       "1  21.894017    1.103001       0.514236        0.521126  0.633761  0.638298   \n",
+       "2  22.849393    1.074077       0.514883        0.521407  0.641219  0.644272   \n",
+       "3  21.055260    1.036505       0.514507        0.521414  0.638745  0.642847   \n",
+       "4  -0.620605    1.067572       0.513769        0.521541  0.631610  0.641667   \n",
+       "\n",
+       "   test_precision  train_precision  test_recall  train_recall  test_roc_auc  \\\n",
+       "0        0.515979         0.519364     0.819556      0.843800      0.513194   \n",
+       "1        0.515992         0.520282     0.821185      0.825562      0.512013   \n",
+       "2        0.515886         0.519928     0.846992      0.846784      0.510649   \n",
+       "3        0.515818         0.520062     0.838594      0.841528      0.513798   \n",
+       "4        0.515832         0.520255     0.814402      0.836996      0.512235   \n",
+       "\n",
+       "   train_roc_auc  test_neg_log_loss  train_neg_log_loss  test_neg_brier_score  \\\n",
+       "0       0.524244          -0.757911           -0.689198             -0.250998   \n",
+       "1       0.525087          -0.826486           -0.689107             -0.251993   \n",
+       "2       0.525496          -0.853786           -0.688600             -0.252847   \n",
+       "3       0.525427          -0.735036           -0.689149             -0.250659   \n",
+       "4       0.525106          -0.769125           -0.689139             -0.251287   \n",
+       "\n",
+       "   train_neg_brier_score  \n",
+       "0              -0.248362  \n",
+       "1              -0.248325  \n",
+       "2              -0.248141  \n",
+       "3              -0.248321  \n",
+       "4              -0.248325  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "pd.DataFrame(d3_dict)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>fit_time</th>\n",
+       "      <th>score_time</th>\n",
+       "      <th>test_accuracy</th>\n",
+       "      <th>train_accuracy</th>\n",
+       "      <th>test_f1</th>\n",
+       "      <th>train_f1</th>\n",
+       "      <th>test_precision</th>\n",
+       "      <th>train_precision</th>\n",
+       "      <th>test_recall</th>\n",
+       "      <th>train_recall</th>\n",
+       "      <th>test_roc_auc</th>\n",
+       "      <th>train_roc_auc</th>\n",
+       "      <th>test_neg_log_loss</th>\n",
+       "      <th>train_neg_log_loss</th>\n",
+       "      <th>test_neg_brier_score</th>\n",
+       "      <th>train_neg_brier_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>20.939348</td>\n",
+       "      <td>1.048407</td>\n",
+       "      <td>0.514161</td>\n",
+       "      <td>0.520378</td>\n",
+       "      <td>0.633248</td>\n",
+       "      <td>0.642962</td>\n",
+       "      <td>0.515978</td>\n",
+       "      <td>0.519359</td>\n",
+       "      <td>0.819504</td>\n",
+       "      <td>0.843774</td>\n",
+       "      <td>0.513196</td>\n",
+       "      <td>0.524226</td>\n",
+       "      <td>-0.758860</td>\n",
+       "      <td>-0.689209</td>\n",
+       "      <td>-0.250993</td>\n",
+       "      <td>-0.248366</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>21.938565</td>\n",
+       "      <td>1.076686</td>\n",
+       "      <td>0.514218</td>\n",
+       "      <td>0.521134</td>\n",
+       "      <td>0.633790</td>\n",
+       "      <td>0.638303</td>\n",
+       "      <td>0.515978</td>\n",
+       "      <td>0.520287</td>\n",
+       "      <td>0.821319</td>\n",
+       "      <td>0.825566</td>\n",
+       "      <td>0.511975</td>\n",
+       "      <td>0.525104</td>\n",
+       "      <td>-0.827558</td>\n",
+       "      <td>-0.689099</td>\n",
+       "      <td>-0.252012</td>\n",
+       "      <td>-0.248322</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>22.727627</td>\n",
+       "      <td>1.050080</td>\n",
+       "      <td>0.514874</td>\n",
+       "      <td>0.521402</td>\n",
+       "      <td>0.641204</td>\n",
+       "      <td>0.644261</td>\n",
+       "      <td>0.515882</td>\n",
+       "      <td>0.519926</td>\n",
+       "      <td>0.846953</td>\n",
+       "      <td>0.846754</td>\n",
+       "      <td>0.510631</td>\n",
+       "      <td>0.525487</td>\n",
+       "      <td>-0.854158</td>\n",
+       "      <td>-0.688607</td>\n",
+       "      <td>-0.252851</td>\n",
+       "      <td>-0.248144</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>43.371215</td>\n",
+       "      <td>-21.134520</td>\n",
+       "      <td>0.514496</td>\n",
+       "      <td>0.521410</td>\n",
+       "      <td>0.638741</td>\n",
+       "      <td>0.642844</td>\n",
+       "      <td>0.515811</td>\n",
+       "      <td>0.520060</td>\n",
+       "      <td>0.838597</td>\n",
+       "      <td>0.841525</td>\n",
+       "      <td>0.513758</td>\n",
+       "      <td>0.525439</td>\n",
+       "      <td>-0.735040</td>\n",
+       "      <td>-0.689151</td>\n",
+       "      <td>-0.250660</td>\n",
+       "      <td>-0.248321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>21.453695</td>\n",
+       "      <td>1.036586</td>\n",
+       "      <td>0.513765</td>\n",
+       "      <td>0.521532</td>\n",
+       "      <td>0.631611</td>\n",
+       "      <td>0.641672</td>\n",
+       "      <td>0.515829</td>\n",
+       "      <td>0.520249</td>\n",
+       "      <td>0.814413</td>\n",
+       "      <td>0.837032</td>\n",
+       "      <td>0.512235</td>\n",
+       "      <td>0.525088</td>\n",
+       "      <td>-0.768537</td>\n",
+       "      <td>-0.689141</td>\n",
+       "      <td>-0.251269</td>\n",
+       "      <td>-0.248326</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    fit_time  score_time  test_accuracy  train_accuracy   test_f1  train_f1  \\\n",
+       "0  20.939348    1.048407       0.514161        0.520378  0.633248  0.642962   \n",
+       "1  21.938565    1.076686       0.514218        0.521134  0.633790  0.638303   \n",
+       "2  22.727627    1.050080       0.514874        0.521402  0.641204  0.644261   \n",
+       "3  43.371215  -21.134520       0.514496        0.521410  0.638741  0.642844   \n",
+       "4  21.453695    1.036586       0.513765        0.521532  0.631611  0.641672   \n",
+       "\n",
+       "   test_precision  train_precision  test_recall  train_recall  test_roc_auc  \\\n",
+       "0        0.515978         0.519359     0.819504      0.843774      0.513196   \n",
+       "1        0.515978         0.520287     0.821319      0.825566      0.511975   \n",
+       "2        0.515882         0.519926     0.846953      0.846754      0.510631   \n",
+       "3        0.515811         0.520060     0.838597      0.841525      0.513758   \n",
+       "4        0.515829         0.520249     0.814413      0.837032      0.512235   \n",
+       "\n",
+       "   train_roc_auc  test_neg_log_loss  train_neg_log_loss  test_neg_brier_score  \\\n",
+       "0       0.524226          -0.758860           -0.689209             -0.250993   \n",
+       "1       0.525104          -0.827558           -0.689099             -0.252012   \n",
+       "2       0.525487          -0.854158           -0.688607             -0.252851   \n",
+       "3       0.525439          -0.735040           -0.689151             -0.250660   \n",
+       "4       0.525088          -0.768537           -0.689141             -0.251269   \n",
+       "\n",
+       "   train_neg_brier_score  \n",
+       "0              -0.248366  \n",
+       "1              -0.248322  \n",
+       "2              -0.248144  \n",
+       "3              -0.248321  \n",
+       "4              -0.248326  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "d15_dict = cross_validate(pipe_d15, X, Y, cv=5, scoring = scoring, return_train_score = True)\n",
     "pd.DataFrame(d15_dict)"
@@ -545,9 +2855,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "fit_time                 26.086090\n",
+       "score_time               -3.384552\n",
+       "test_accuracy             0.514303\n",
+       "train_accuracy            0.521171\n",
+       "test_f1                   0.635719\n",
+       "train_f1                  0.642009\n",
+       "test_precision            0.515896\n",
+       "train_precision           0.519976\n",
+       "test_recall               0.828157\n",
+       "train_recall              0.838930\n",
+       "test_roc_auc              0.512359\n",
+       "train_roc_auc             0.525069\n",
+       "test_neg_log_loss        -0.788831\n",
+       "train_neg_log_loss       -0.689042\n",
+       "test_neg_brier_score     -0.251557\n",
+       "train_neg_brier_score    -0.248296\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "pd.DataFrame(d15_dict).mean()"
    ]
@@ -555,7 +2892,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "env",
+   "display_name": "dsi_participant",
    "language": "python",
    "name": "python3"
   },
@@ -569,7 +2906,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index 0825486c4..0e787b5c7 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -26,19 +26,67 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "../../05_src/data/prices/\n"
+     ]
+    }
+   ],
    "source": [
     "# Write your code below.\n",
-    "\n"
+    "\n",
+    "# Import dotenv\n",
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "\n",
+    "# Load the environment variables\n",
+    "load_dotenv()\n",
+    "price_data_dir = os.getenv(\"PRICE_DATA\")\n",
+    "\n",
+    "# Check if PRICE_DATA loaded correctly from dotenv\n",
+    "print(price_data_dir)  # Should output the path to PRICE_DATA"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_56322/676544213.py:1: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \n",
+      "In a future release, Dask DataFrame will use new implementation that\n",
+      "contains several improvements including a logical query planning.\n",
+      "The user-facing DataFrame API will remain unchanged.\n",
+      "\n",
+      "The new implementation is already available and can be enabled by\n",
+      "installing the dask-expr library:\n",
+      "\n",
+      "    $ pip install dask-expr\n",
+      "\n",
+      "and turning the query planning option on:\n",
+      "\n",
+      "    >>> import dask\n",
+      "    >>> dask.config.set({'dataframe.query-planning': True})\n",
+      "    >>> import dask.dataframe as dd\n",
+      "\n",
+      "API documentation for the new implementation is available at\n",
+      "https://docs.dask.org/en/stable/dask-expr-api.html\n",
+      "\n",
+      "Any feedback can be reported on the Dask issue tracker\n",
+      "https://github.com/dask/dask/issues \n",
+      "\n",
+      "  import dask.dataframe as dd\n"
+     ]
+    }
+   ],
    "source": [
     "import dask.dataframe as dd"
    ]
@@ -57,13 +105,170 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loaded columns: Index(['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume', 'sector',\n",
+      "       'subsector', 'year'],\n",
+      "      dtype='object')\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>sector</th>\n",
+       "      <th>subsector</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ticker</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2000-01-03</td>\n",
+       "      <td>56.330471</td>\n",
+       "      <td>56.464592</td>\n",
+       "      <td>48.193848</td>\n",
+       "      <td>51.502148</td>\n",
+       "      <td>43.463024</td>\n",
+       "      <td>4674353</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Life Sciences Tools &amp; Services</td>\n",
+       "      <td>2000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2000-01-04</td>\n",
+       "      <td>48.730328</td>\n",
+       "      <td>49.266811</td>\n",
+       "      <td>46.316166</td>\n",
+       "      <td>47.567955</td>\n",
+       "      <td>40.142933</td>\n",
+       "      <td>4765083</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Life Sciences Tools &amp; Services</td>\n",
+       "      <td>2000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2000-01-05</td>\n",
+       "      <td>47.389126</td>\n",
+       "      <td>47.567955</td>\n",
+       "      <td>43.141991</td>\n",
+       "      <td>44.617310</td>\n",
+       "      <td>37.652870</td>\n",
+       "      <td>5758642</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Life Sciences Tools &amp; Services</td>\n",
+       "      <td>2000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2000-01-06</td>\n",
+       "      <td>44.080830</td>\n",
+       "      <td>44.349072</td>\n",
+       "      <td>41.577251</td>\n",
+       "      <td>42.918453</td>\n",
+       "      <td>36.219185</td>\n",
+       "      <td>2534434</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Life Sciences Tools &amp; Services</td>\n",
+       "      <td>2000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>2000-01-07</td>\n",
+       "      <td>42.247852</td>\n",
+       "      <td>47.165592</td>\n",
+       "      <td>42.203148</td>\n",
+       "      <td>46.494991</td>\n",
+       "      <td>39.237453</td>\n",
+       "      <td>2819626</td>\n",
+       "      <td>Health Care</td>\n",
+       "      <td>Life Sciences Tools &amp; Services</td>\n",
+       "      <td>2000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Date       Open       High        Low      Close  Adj Close  \\\n",
+       "ticker                                                                     \n",
+       "A      2000-01-03  56.330471  56.464592  48.193848  51.502148  43.463024   \n",
+       "A      2000-01-04  48.730328  49.266811  46.316166  47.567955  40.142933   \n",
+       "A      2000-01-05  47.389126  47.567955  43.141991  44.617310  37.652870   \n",
+       "A      2000-01-06  44.080830  44.349072  41.577251  42.918453  36.219185   \n",
+       "A      2000-01-07  42.247852  47.165592  42.203148  46.494991  39.237453   \n",
+       "\n",
+       "         Volume       sector                       subsector  year  \n",
+       "ticker                                                              \n",
+       "A       4674353  Health Care  Life Sciences Tools & Services  2000  \n",
+       "A       4765083  Health Care  Life Sciences Tools & Services  2000  \n",
+       "A       5758642  Health Care  Life Sciences Tools & Services  2000  \n",
+       "A       2534434  Health Care  Life Sciences Tools & Services  2000  \n",
+       "A       2819626  Health Care  Life Sciences Tools & Services  2000  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "import os\n",
     "from glob import glob\n",
     "\n",
     "# Write your code below.\n",
-    "\n"
+    "\n",
+    "# Step 1: Load all parquet files into a single DataFrame\n",
+    "parquet_files = glob(os.path.join(price_data_dir, \"**\", \"*.parquet\"), recursive=True)\n",
+    "parquet_files = [f for f in parquet_files if os.path.isfile(f)]\n",
+    "\n",
+    "# Load data without transformations, just to verify structure\n",
+    "df = dd.read_parquet(parquet_files, engine=\"pyarrow\")\n",
+    "\n",
+    "# Step 2: Verify loaded columns and initial rows\n",
+    "print(\"Loaded columns:\", df.columns)\n",
+    "df.head()"
    ]
   },
   {
@@ -88,11 +293,224188 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+      "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+      "  Before: .shift(1)\n",
+      "  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+      "  or:     .shift(1, meta=('x', 'f8'))            for series result\n",
+      "  df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+      "Exception ignored in: <bound method IPythonKernel._clean_thread_parent_frames of <ipykernel.ipkernel.IPythonKernel object at 0x7fb964377070>>\n",
+      "Traceback (most recent call last):\n",
+      "  File \"/home/alex8642/miniconda3/envs/dsi_participant/lib/python3.9/site-packages/ipykernel/ipkernel.py\", line 775, in _clean_thread_parent_frames\n",
+      "    def _clean_thread_parent_frames(\n",
+      "KeyboardInterrupt: \n"
+     ]
+    }
+   ],
    "source": [
     "# Write your code below.\n",
+    "\n",
+    "# List to hold each individual processed DataFrame\n",
+    "processed_dfs = []\n",
+    "\n",
+    "# Loop through each parquet file and process individually\n",
+    "parquet_files = glob(os.path.join(price_data_dir, \"**\", \"*.parquet\"), recursive=True)\n",
+    "for file in parquet_files:\n",
+    "    # Load each file individually\n",
+    "    df = dd.read_parquet(file, engine=\"pyarrow\")\n",
+    "    \n",
+    "    # Perform groupby operations within each file, without any cross-file duplicates\n",
+    "    df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+    "    df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+    "    df['returns'] = (df['Adj Close'] / df['Adj_Close_lag']) - 1\n",
+    "    df['hi_lo_range'] = df['High'] - df['Low']\n",
+    "    \n",
+    "    # Append the processed DataFrame to the list\n",
+    "    processed_dfs.append(df)\n",
+    "\n",
+    "# Concatenate all processed DataFrames into a single Dask DataFrame\n",
+    "dd_feat = dd.concat(processed_dfs)\n",
+    "\n",
+    "# Verify the result\n",
+    "dd_feat.head()\n",
+    "\n",
     "\n"
    ]
   },
@@ -166,7 +224548,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "env",
+   "display_name": "dsi_participant",
    "language": "python",
    "name": "python3"
   },
@@ -180,7 +224562,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,